209,526 results
Search Results
2. A fully-automated paper ECG digitisation algorithm using deep learning.
- Author
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Wu, Huiyi, Patel, Kiran Haresh Kumar, Li, Xinyang, Zhang, Bowen, Galazis, Christoforos, Bajaj, Nikesh, Sau, Arunashis, Shi, Xili, Sun, Lin, Tao, Yanda, Al-Qaysi, Harith, Tarusan, Lawrence, Yasmin, Najira, Grewal, Natasha, Kapoor, Gaurika, Waks, Jonathan W., Kramer, Daniel B., Peters, Nicholas S., and Ng, Fu Siong
- Subjects
DEEP learning ,ELECTROCARDIOGRAPHY ,ELECTRONIC paper ,ATRIAL fibrillation ,ALGORITHMS ,HEART failure ,HEART rate monitors - Abstract
There is increasing focus on applying deep learning methods to electrocardiograms (ECGs), with recent studies showing that neural networks (NNs) can predict future heart failure or atrial fibrillation from the ECG alone. However, large numbers of ECGs are needed to train NNs, and many ECGs are currently only in paper format, which are not suitable for NN training. We developed a fully-automated online ECG digitisation tool to convert scanned paper ECGs into digital signals. Using automated horizontal and vertical anchor point detection, the algorithm automatically segments the ECG image into separate images for the 12 leads and a dynamical morphological algorithm is then applied to extract the signal of interest. We then validated the performance of the algorithm on 515 digital ECGs, of which 45 were printed, scanned and redigitised. The automated digitisation tool achieved 99.0% correlation between the digitised signals and the ground truth ECG (n = 515 standard 3-by-4 ECGs) after excluding ECGs with overlap of lead signals. Without exclusion, the performance of average correlation was from 90 to 97% across the leads on all 3-by-4 ECGs. There was a 97% correlation for 12-by-1 and 3-by-1 ECG formats after excluding ECGs with overlap of lead signals. Without exclusion, the average correlation of some leads in 12-by-1 ECGs was 60–70% and the average correlation of 3-by-1 ECGs achieved 80–90%. ECGs that were printed, scanned, and redigitised, our tool achieved 96% correlation with the original signals. We have developed and validated a fully-automated, user-friendly, online ECG digitisation tool. Unlike other available tools, this does not require any manual segmentation of ECG signals. Our tool can facilitate the rapid and automated digitisation of large repositories of paper ECGs to allow them to be used for deep learning projects. [ABSTRACT FROM AUTHOR]
- Published
- 2022
- Full Text
- View/download PDF
3. A Machine Learning Model to Predict Citation Counts of Scientific Papers in Otology Field.
- Author
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Alohali, Yousef A., Fayed, Mahmoud S., Mesallam, Tamer, Abdelsamad, Yassin, Almuhawas, Fida, and Hagr, Abdulrahman
- Subjects
DECISION trees ,SERIAL publications ,NATURAL language processing ,BIBLIOMETRICS ,MACHINE learning ,REGRESSION analysis ,RANDOM forest algorithms ,CITATION analysis ,DESCRIPTIVE statistics ,PREDICTION models ,ARTIFICIAL neural networks ,MEDICAL research ,MEDICAL specialties & specialists ,ALGORITHMS - Abstract
One of the most widely used measures of scientific impact is the number of citations. However, due to its heavy-tailed distribution, citations are fundamentally difficult to predict but can be improved. This study was aimed at investigating the factors and parts influencing the citation number of a scientific paper in the otology field. Therefore, this work proposes a new solution that utilizes machine learning and natural language processing to process English text and provides a paper citation as the predicted results. Different algorithms are implemented in this solution, such as linear regression, boosted decision tree, decision forest, and neural networks. The application of neural network regression revealed that papers' abstracts have more influence on the citation numbers of otological articles. This new solution has been developed in visual programming using Microsoft Azure machine learning at the back end and Programming Without Coding Technology at the front end. We recommend using machine learning models to improve the abstracts of research articles to get more citations. [ABSTRACT FROM AUTHOR]
- Published
- 2022
- Full Text
- View/download PDF
4. Efficient and Effective Academic Expert Finding on Heterogeneous Graphs through (k, P)-Core based Embedding.
- Author
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YUXIANG WANG, JUN LIU, XIAOLIANG XU, XIANGYU KE, TIANXING WU, and XIAOXUAN GOU
- Subjects
COMMUNITIES ,SEMANTICS ,ALGORITHMS - Abstract
Expert finding is crucial for a wealth of applications in both academia and industry. Given a user query and trove of academic papers, expert finding aims at retrieving the most relevant experts for the query, from the academic papers. Existing studies focus on embedding-based solutions that consider academic papers’ textual semantic similarities to a query via document representation and extract the top-n experts from the most similar papers. Beyond implicit textual semantics, however, papers’ explicit relationships (e.g., co-authorship) in a heterogeneous graph (e.g., DBLP) are critical for expert finding, because they help improve the representation quality. Despite their importance, the explicit relationships of papers generally have been ignored in the literature. In this article, we study expert finding on heterogeneous graphs by considering both the explicit relationships and implicit textual semantics of papers in one model. Specifically, we define the cohesive (k, P)-core community of papers w.r.t. a meta-path P (i.e., relationship) and propose a (k, P)-core based document embedding model to enhance the representation quality. Based on this, we design a proximity graph-based index (PGIndex) of papers and present a threshold algorithm (TA)-based method to efficiently extract top-n experts from papers returned by PG-Index. We further optimize our approach in two ways: (1) we boost effectiveness by considering the (k, P)-core community of experts and the diversity of experts’ research interests, to achieve high-quality expert representation from paper representation; and (2) we streamline expert finding, going from “extract top-n experts from top-m (m > n) semantically similar papers” to “directly return top-n experts”. The process of returning a large number of top-m papers as intermediate data is avoided, thereby improving the efficiency. Extensive experiments using real-world datasets demonstrate our approach’s superiority. [ABSTRACT FROM AUTHOR]
- Published
- 2023
- Full Text
- View/download PDF
5. Cost Optimal Production-Scheduling Model Based on VNS-NSGA-II Hybrid Algorithm—Study on Tissue Paper Mill.
- Author
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Zhang, Huanhuan, Li, Jigeng, Hong, Mengna, Man, Yi, and He, Zhenglei
- Subjects
PAPER mills ,FLOW shop scheduling ,PRODUCTION scheduling ,INDUSTRIAL costs ,ALGORITHMS - Abstract
With the development of the customization concept, small-batch and multi-variety production will become one of the major production modes, especially for fast-moving consumer goods. However, this production mode has two issues: high production cost and the long manufacturing period. To address these issues, this study proposes a multi-objective optimization model for the flexible flow-shop to optimize the production scheduling, which would maximize the production efficiency by minimizing the production cost and makespan. The model is designed based on hybrid algorithms, which combine a fast non-dominated genetic algorithm (NSGA-II) and a variable neighborhood search algorithm (VNS). In this model, NSGA-II is the major algorithm to calculate the optimal solutions. VNS is to improve the quality of the solution obtained by NSGA-II. The model is verified by an example of a real-world typical FFS, a tissue papermaking mill. The results show that the scheduling model can reduce production costs by 4.2% and makespan by 6.8% compared with manual scheduling. The hybrid VNS-NSGA-II model also shows better performance than NSGA-II, both in production cost and makespan. Hybrid algorithms are a good solution for multi-objective optimization issues in flexible flow-shop production scheduling. [ABSTRACT FROM AUTHOR]
- Published
- 2022
- Full Text
- View/download PDF
6. Research on the Fusion of Hybrid Fuzzy Clustering Algorithm and Computer Automatic Test Paper Composition Algorithm.
- Author
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Kan, Baopeng
- Subjects
COMPUTERS ,COMPUTER algorithms ,FUZZY algorithms ,COMPUTER workstation clusters ,ALGORITHMS ,HIGHER education exams - Abstract
In order to improve the effect of intelligent automatic test paper composition, this paper combines the hybrid fuzzy clustering algorithm to study the computer automatic test paper composition algorithm. In this paper, a computer automatic test paper composition system based on hybrid fuzzy clustering algorithm is constructed. Moreover, the hybrid fuzzy clustering method used in this paper is used as the basic algorithm of the system, and the algorithm is improved according to the actual needs of intelligent paper composition. In addition, this paper uses an intelligent algorithm to input the relevant constraint parameters and combines the original parameters to select the most suitable test questions from the database and combine them into test papers. Finally, this paper constructs the system structure based on the requirements of intelligent test paper composition. The experimental research shows that the computer automatic test paper composition system based on the hybrid fuzzy clustering algorithm proposed in this paper has a good test paper composition function, which can effectively promote the progress of the intelligent examination mode in colleges and universities. [ABSTRACT FROM AUTHOR]
- Published
- 2022
- Full Text
- View/download PDF
7. Wet Paper Coding-Based Deep Neural Network Watermarking
- Author
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Xuan Wang, Yuliang Lu, Xuehu Yan, and Long Yu
- Subjects
Neural Networks, Computer ,Electrical and Electronic Engineering ,Biochemistry ,Instrumentation ,deep neural network ,watermarking ,wet paper encoding ,embedding rate ,Atomic and Molecular Physics, and Optics ,Algorithms ,Computer Security ,Analytical Chemistry - Abstract
In recent years, the wide application of deep neural network models has brought serious risks of intellectual property rights infringement. Embedding a watermark in a network model is an effective solution to protect intellectual property rights. Although researchers have proposed schemes to add watermarks to models, they cannot prevent attackers from adding and overwriting original information, and embedding rates cannot be quantified. Therefore, aiming at these problems, this paper designs a high embedding rate and tamper-proof watermarking scheme. We employ wet paper coding (WPC), in which important parameters are regarded as wet blocks and the remaining unimportant parameters are regarded as dry blocks in the model. To obtain the important parameters more easily, we propose an optimized probabilistic selection strategy (OPSS). OPSS defines the unimportant-level function and sets the importance threshold to select the important parameter positions and to ensure that the original function is not affected after the model parameters are changed. We regard important parameters as an unmodifiable part, and only modify the part that includes the unimportant parameters. We selected the MNIST, CIFAR-10, and ImageNet datasets to test the performance of the model after adding a watermark and to analyze the fidelity, robustness, embedding rate, and comparison schemes of the model. Our experiment shows that the proposed scheme has high fidelity and strong robustness along with a high embedding rate and the ability to prevent malicious tampering.
- Published
- 2022
8. Tools and algorithms for the construction and analysis of systems: a special issue on tool papers for TACAS 2021.
- Author
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Jensen, Peter Gjøl and Neele, Thomas
- Subjects
ALGORITHMS ,SOFTWARE verification ,INTEGRATED circuit verification ,SYSTEMS software ,CONFERENCES & conventions - Abstract
This special issue contains six revised and extended versions of tool papers that appeared in the proceedings of TACAS 2021, the 27th International Conference on Tools and Algorithms for the Construction and Analysis of Systems. The issue is dedicated to the realization of algorithms in tools and the studies of the application of these tools for analysing hard- and software systems. [ABSTRACT FROM AUTHOR]
- Published
- 2023
- Full Text
- View/download PDF
9. Socio‐technical issues in the platform‐mediated gig economy: A systematic literature review: An Annual Review of Information Science and Technology (ARIST) paper.
- Author
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Dedema, Meredith and Rosenbaum, Howard
- Subjects
INFORMATION science ,TECHNOLOGY ,CORPORATE culture ,ALGORITHMS ,ECONOMICS - Abstract
The gig economy and gig work have grown quickly in recent years and have drawn much attention from researchers in different fields. Because the platform mediated gig economy is a relatively new phenomenon, studies have produced a range of interesting findings; of interest here are the socio‐technical issues that this work has surfaced. This systematic literature review (SLR) provides a snapshot of a range of socio‐technical issues raised in the last 12 years of literature focused on the platform mediated gig economy. Based on a sample of 515 papers gathered from nine databases in multiple disciplines, 132 were coded that specifically studied the gig economy, gig work, and gig workers. Three main socio‐technical themes were identified: (1) the digital workplace, which includes information infrastructure and digital labor that are related to the nature of gig work and the user agency; (2) algorithmic management, which includes platform governance, performance management, information asymmetry, power asymmetry, and system manipulation, relying on a diverse set of technological tools including algorithms and big data analytics; (3) ethical design, as a relevant value set that gig workers expect from the platform, which includes trust, fairness, equality, privacy, and transparency. A social informatics perspective is used to rethink the relationship between gig workers and platforms, extract the socio‐technical issues noted in prior research, and discuss the underexplored aspects of the platform mediated gig economy. The results draw attention to understudied yet critically important socio‐technical issues in the gig economy that suggest short‐ and long‐term opportunities for future research directions. [ABSTRACT FROM AUTHOR]
- Published
- 2024
- Full Text
- View/download PDF
10. The molecular basis of socially mediated phenotypic plasticity in a eusocial paper wasp
- Author
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Max Reuter, Benjamin A. Taylor, Seirian Sumner, Alessandro Cini, and Christopher D. R. Wyatt
- Subjects
0106 biological sciences ,0301 basic medicine ,Bioinformatics ,Science ,Wasps ,education ,Gene regulatory network ,General Physics and Astronomy ,Polistes dominula ,010603 evolutionary biology ,01 natural sciences ,Article ,General Biochemistry, Genetics and Molecular Biology ,Machine Learning ,03 medical and health sciences ,Gene expression ,Animals ,Humans ,Gene Regulatory Networks ,Social Behavior ,Paper wasp ,Phenotypic plasticity ,Multidisciplinary ,biology ,Gene Expression Profiling ,Computational Biology ,General Chemistry ,Animal behaviour ,biology.organism_classification ,Adaptation, Physiological ,Phenotype ,Eusociality ,Gene Ontology ,030104 developmental biology ,Evolutionary biology ,Female ,Adaptation ,Transcriptome ,Entomology ,Algorithms - Abstract
Phenotypic plasticity, the ability to produce multiple phenotypes from a single genotype, represents an excellent model with which to examine the relationship between gene expression and phenotypes. Analyses of the molecular foundations of phenotypic plasticity are challenging, however, especially in the case of complex social phenotypes. Here we apply a machine learning approach to tackle this challenge by analyzing individual-level gene expression profiles of Polistes dominula paper wasps following the loss of a queen. We find that caste-associated gene expression profiles respond strongly to queen loss, and that this change is partly explained by attributes such as age but occurs even in individuals that appear phenotypically unaffected. These results demonstrate that large changes in gene expression may occur in the absence of outwardly detectable phenotypic changes, resulting here in a socially mediated de-differentiation of individuals at the transcriptomic level but not at the levels of ovarian development or behavior., Connecting genotypes to complex social behaviour is challenging. Taylor et al. use machine learning to show a strong response of caste-associated gene expression to queen loss, wherein individual wasp’s expression profiles become intermediate between queen and worker states, even in the absence of behavioural changes.
- Published
- 2021
11. A mathematical foundation for foundation paper pieceable quilts.
- Author
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Leake, Mackenzie, Bernstein, Gilbert, Davis, Abe, and Agrawala, Maneesh
- Subjects
QUILTS ,QUILTING ,PATCHWORK quilts ,SEWING patterns ,ALGORITHMS - Abstract
Foundation paper piecing is a popular technique for constructing fabric patchwork quilts using printed paper patterns. But, the construction process imposes constraints on the geometry of the pattern and the order in which the fabric pieces are attached to the quilt. Manually designing foundation paper pieceable patterns that meet all of these constraints is challenging. In this work we mathematically formalize the foundation paper piecing process and use this formalization to develop an algorithm that can automatically check if an input pattern geometry is foundation paper pieceable. Our key insight is that we can represent the geometric pattern design using a certain type of dual hypergraph where nodes represent faces and hyperedges represent seams connecting two or more nodes. We show that determining whether the pattern is paper pieceable is equivalent to checking whether this hypergraph is acyclic, and if it is acyclic, we can apply a leaf-plucking algorithm to the hypergraph to generate viable sewing orders for the pattern geometry. We implement this algorithm in a design tool that allows quilt designers to focus on producing the geometric design of their pattern and let the tool handle the tedious task of determining whether the pattern is foundation paper pieceable. [ABSTRACT FROM AUTHOR]
- Published
- 2021
- Full Text
- View/download PDF
12. Performance Evaluation of the Extractive Methods in Automatic Text Summarization Using Medical Papers.
- Author
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Kus, Anil and Aci, Cigdem Inan
- Subjects
PERFORMANCE evaluation ,TEXT summarization ,MEDICAL sciences ,ALGORITHMS ,SEMANTICS - Abstract
Copyright of Gazi Journal of Engineering Sciences (GJES) / Gazi Mühendislik Bilimleri Dergisi is the property of Gazi Journal of Engineering Sciences and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
- Published
- 2023
- Full Text
- View/download PDF
13. A Machine Learning Model to Predict Citation Counts of Scientific Papers in Otology Field
- Author
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Yousef A. Alohali, Mahmoud S. Fayed, Tamer Mesallam, Yassin Abdelsamad, Fida Almuhawas, and Abdulrahman Hagr
- Subjects
Machine Learning ,Otolaryngology ,Article Subject ,General Immunology and Microbiology ,Linear Models ,General Medicine ,Algorithms ,General Biochemistry, Genetics and Molecular Biology - Abstract
One of the most widely used measures of scientific impact is the number of citations. However, due to its heavy-tailed distribution, citations are fundamentally difficult to predict but can be improved. This study was aimed at investigating the factors and parts influencing the citation number of a scientific paper in the otology field. Therefore, this work proposes a new solution that utilizes machine learning and natural language processing to process English text and provides a paper citation as the predicted results. Different algorithms are implemented in this solution, such as linear regression, boosted decision tree, decision forest, and neural networks. The application of neural network regression revealed that papers’ abstracts have more influence on the citation numbers of otological articles. This new solution has been developed in visual programming using Microsoft Azure machine learning at the back end and Programming Without Coding Technology at the front end. We recommend using machine learning models to improve the abstracts of research articles to get more citations.
- Published
- 2022
14. Scientific papers and artificial intelligence. Brave new world?
- Author
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Nexøe, Jørgen
- Subjects
COMPUTERS ,MANUSCRIPTS ,ARTIFICIAL intelligence ,MACHINE learning ,DATA analysis ,MEDICAL literature ,MEDICAL research ,ALGORITHMS - Published
- 2023
- Full Text
- View/download PDF
15. Discussion paper: implications for the further development of the successfully in emergency medicine implemented AUD2IT-algorithm.
- Author
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Przestrzelski, Christopher, Jakob, Antonina, Jakob, Clemens, and Hoffmann, Felix R.
- Subjects
DOCUMENTATION ,CURRICULUM ,HUMAN services programs ,EMERGENCY medicine ,EXPERIENCE ,MEDICAL records ,ELECTRONIC publications ,ALGORITHMS ,PATIENTS' attitudes - Abstract
The AUD2IT-algorithm is a tool to structure the data, which is collected during an emergency treatment. The goal is on the one hand to structure the documentation of the data and on the other hand to give a standardised data structure for the report during handover of an emergency patient. AUD2IT-algorithm was developed to provide residents a documentation aid, which helps to structure the medical reports without getting lost in unimportant details or forgetting important information. The sequence of anamnesis, clinical examination, considering a differential diagnosis, technical diagnostics, interpretation and therapy is rather an academic classification than a description of the real workflow. In a real setting, most of these steps take place simultaneously. Therefore, the application of the AUD2IT-algorithm should also be carried out according to the real processes. A big advantage of the AUD2IT-algorithm is that it can be used as a structure for the entire treatment process and also is entirely usable as a handover protocol within this process to make sure, that the existing state of knowledge is ensured at each point of a team-timeout. PR-E-(AUD2IT)-algorithm makes it possible to document a treatment process that, in principle, does not have to be limited to the field of emergency medicine. Also, in the outpatient treatment the PR-E-(AUD2IT)-algorithm could be used and further developed. One example could be the preparation and allocation of needed resources at the general practitioner. The algorithm is a standardised tool that can be used by healthcare professionals of any level of training. It gives the user a sense of security in their daily work. [ABSTRACT FROM AUTHOR]
- Published
- 2024
- Full Text
- View/download PDF
16. Digitalized Control Algorithm of Bridgeless Totem-Pole PFC with a Simple Control Structure Based on the Phase Angle.
- Author
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Lee, Gi-Young, Park, Hae-Chan, Ji, Min-Woo, and Kim, Rae-Young
- Subjects
ELECTRIC current rectifiers ,ELECTRONIC paper ,PHASE-locked loops ,ALGORITHMS ,ANGLES ,VOLTAGE - Abstract
Compared to the conventional boost power factor correction (PFC) converter, a totem-pole bridgeless PFC has high efficiency because it does not have an input diode rectifier stage, but a current spike may occur when the polarity of the grid voltage changes. This paper proposes a digital control algorithm for bridgeless totem-pole PFC with a simple control structure based on the phase angle of grid voltage. The proposed algorithm has a PI-based double-loop control structure and performs DC-link voltage and input inductor current control. Rectifying switches operate based on the proposed rectification algorithm using phase angle information calculated through a single-phase phase-locked loop (PLL) to prevent current spikes. The feed-forward duty ratio value is calculated according to the polarity of the grid voltage and added to the double-loop controller to perform appropriate power factor control. The performance and feasibility of the proposed control algorithm are verified through a 3 kW hardware prototype. [ABSTRACT FROM AUTHOR]
- Published
- 2023
- Full Text
- View/download PDF
17. Visualization Display System of Gannan Hakka Paper-Cut Works Based on Computer Graphics Algorithm
- Author
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Xingping Li
- Subjects
Article Subject ,General Computer Science ,General Mathematics ,General Neuroscience ,Computer Graphics ,Image Processing, Computer-Assisted ,General Medicine ,Algorithms - Abstract
Today, computer graphics and graphic image processing techniques have been widely used in daily life and industrial production. Due to the development of computers, computer graphics has brought more convenience to our daily life. In order to give full play to the value of computers, this paper takes the Hakka paper-cut art with local characteristics as the starting point, first of all its development history, artistic characteristics, compositional forms, expression techniques, cultural connotations, Hakka paper-cut patterns, and the symbolic meaning of folk customs, and then we design a visualization system for the paper-cut works of Gannan Hakka based on computer graphics. In addition, the system provides a solution for the integration of Gannan Hakka paper-cut art and Jiangxi native product packaging design and provides a reference for the theory and practice of modern native product packaging design.
- Published
- 2022
18. Hybrid Methods of Bibliographic Coupling and Text Similarity Measurement for Biomedical Paper Recommendation.
- Author
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Hongmei Guo, Zhesi Shen, Jianxun Zeng, and Na Hong
- Subjects
BIBLIOGRAPHY ,CONFERENCES & conventions ,CITATION analysis ,BIBLIOGRAPHICAL citations ,RESEARCH funding ,CONTENT analysis ,ALGORITHMS - Abstract
The amount of available scientific literature is increasing, and studies have proposed various methods for evaluating document-document similarity in order to cluster or classify documents for science mapping and knowledge discovery. In this paper, we propose hybrid methods for bibliographic coupling (BC) and linear evaluation of text or content similarity: We combined BC with BM25, Cosine, and PMRA to compare their performances with single methods in paper recommendation tasks using TREC Genomics Track 2005datasets. For paper recommendation, BC and text-based methods complement each other, and hybrid methods were better than single methods. The combinations of BC with BM25 and BC with Cosine performed better than BC with PMRA. The performances were best when the weights of BM25, Cosine, and PMRA were 0.025, 0.2, and 0.2, respectively, in hybrid methods. For paper recommendation, the combinations of BC with text-based methods were better than BC or text-based methods used alone. The choice of method should depend on the actual data and research needs. In the future, the underlying reasons for the differences in performance and the specific part or type of information they complement in text clustering or recommendation need to be examined. [ABSTRACT FROM AUTHOR]
- Published
- 2021
- Full Text
- View/download PDF
19. Predicting Breast Cancer by Paper Spray Ion Mobility Spectrometry Mass Spectrometry and Machine Learning
- Author
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Ewelina P. Dutkiewicz, Chih-Lin Chen, Hua-Yi Hsieh, Cheng-Chih Hsu, Ying-Chen Huang, Ming-Yang Wang, Hsin-Hsiang Chung, and Bo-Rong Chen
- Subjects
Paper ,Core needle ,Spectrometry, Mass, Electrospray Ionization ,Ion-mobility spectrometry ,Electrospray ionization ,Breast Neoplasms ,010402 general chemistry ,Machine learning ,computer.software_genre ,Mass spectrometry ,01 natural sciences ,Analytical Chemistry ,Machine Learning ,Breast cancer ,Ion Mobility Spectrometry ,medicine ,Humans ,business.industry ,Chemistry ,010401 analytical chemistry ,medicine.disease ,Mass spectrometric ,0104 chemical sciences ,Ion-mobility spectrometry–mass spectrometry ,Female ,Artificial intelligence ,Asymmetric waveform ,business ,computer ,Algorithms - Abstract
Paper spray ionization has been used as a fast sampling/ionization method for the direct mass spectrometric analysis of biological samples at ambient conditions. Here, we demonstrated that by utilizing paper spray ionization-mass spectrometry (PSI-MS) coupled with field asymmetric waveform ion mobility spectrometry (FAIMS), predictive metabolic and lipidomic profiles of routine breast core needle biopsies could be obtained effectively. By the combination of machine learning algorithms and pathological examination reports, we developed a classification model, which has an overall accuracy of 87.5% for an instantaneous differentiation between cancerous and noncancerous breast tissues utilizing metabolic and lipidomic profiles. Our results suggested that paper spray ionization-ion mobility spectrometry-mass spectrometry (PSI-IMS-MS) is a powerful approach for rapid breast cancer diagnosis based on altered metabolic and lipidomic profiles.
- Published
- 2019
20. A fully-automated paper ECG digitisation algorithm using deep learning
- Author
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Huiyi Wu, Kiran Haresh Kumar Patel, Xinyang Li, Bowen Zhang, Christoforos Galazis, Nikesh Bajaj, Arunashis Sau, Xili Shi, Lin Sun, Yanda Tao, Harith Al-Qaysi, Lawrence Tarusan, Najira Yasmin, Natasha Grewal, Gaurika Kapoor, Jonathan W. Waks, Daniel B. Kramer, Nicholas S. Peters, and Fu Siong Ng
- Subjects
Electrocardiography ,Deep Learning ,Multidisciplinary ,Atrial Fibrillation ,Humans ,Neural Networks, Computer ,Algorithms - Abstract
There is increasing focus on applying deep learning methods to electrocardiograms (ECGs), with recent studies showing that neural networks (NNs) can predict future heart failure or atrial fibrillation from the ECG alone. However, large numbers of ECGs are needed to train NNs, and many ECGs are currently only in paper format, which are not suitable for NN training. We developed a fully-automated online ECG digitisation tool to convert scanned paper ECGs into digital signals. Using automated horizontal and vertical anchor point detection, the algorithm automatically segments the ECG image into separate images for the 12 leads and a dynamical morphological algorithm is then applied to extract the signal of interest. We then validated the performance of the algorithm on 515 digital ECGs, of which 45 were printed, scanned and redigitised. The automated digitisation tool achieved 99.0% correlation between the digitised signals and the ground truth ECG (n = 515 standard 3-by-4 ECGs) after excluding ECGs with overlap of lead signals. Without exclusion, the performance of average correlation was from 90 to 97% across the leads on all 3-by-4 ECGs. There was a 97% correlation for 12-by-1 and 3-by-1 ECG formats after excluding ECGs with overlap of lead signals. Without exclusion, the average correlation of some leads in 12-by-1 ECGs was 60–70% and the average correlation of 3-by-1 ECGs achieved 80–90%. ECGs that were printed, scanned, and redigitised, our tool achieved 96% correlation with the original signals. We have developed and validated a fully-automated, user-friendly, online ECG digitisation tool. Unlike other available tools, this does not require any manual segmentation of ECG signals. Our tool can facilitate the rapid and automated digitisation of large repositories of paper ECGs to allow them to be used for deep learning projects.
- Published
- 2022
21. ANMCO POSITION PAPER: Considerations on in-hospital cardiological consultations and cardiology outpatient clinics during the COVID-19 pandemic
- Author
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Enzo Amodeo, Nadia Aspromonte, Pasquale Caldarola, Michele Massimo Gulizia, Massimo Imazio, Furio Colivicchi, Serafina Valente, Stefano Domenicucci, Giuseppina Maura Francese, Andrea Di Lenarda, Domenico Gabrielli, Fortunato Scotto di Uccio, Stefano Urbinati, Manlio Cipriani, Adriano Murrone, and Loris Roncon
- Subjects
medicine.medical_specialty ,2019-20 coronavirus outbreak ,Coronavirus disease 2019 (COVID-19) ,Pneumonia, Viral ,Cardiology ,030204 cardiovascular system & hematology ,Ambulatory Care Facilities ,03 medical and health sciences ,Betacoronavirus ,0302 clinical medicine ,COVID-19 Testing ,Contagion risk ,Cardiological consultations ,Epidemiology ,Pandemic ,medicine ,Cardiology outpatient clinics ,Outpatient clinic ,Humans ,AcademicSubjects/MED00200 ,030212 general & internal medicine ,Personal protective equipment ,Pandemics ,Referral and Consultation ,Infection Control ,business.industry ,Clinical Laboratory Techniques ,SARS-CoV-2 ,COVID-19 ,Articles ,medicine.disease ,Cardiovascular disease ,Telemedicine ,Cardiovascular emergencies ,Cardiovascular Diseases ,Position paper ,Medical emergency ,Cardiology and Cardiovascular Medicine ,business ,Coronavirus Infections ,Algorithms - Abstract
Infections by SARS CoV2 - COVID-19 have become in a short time a worldwide health emergency. Due to cardiovascular implications of COVID-19 and to very frequent previous cardiovascular disorders of COVID-19 patients, it is presently crucial that Cardiologists are fully aware of COVID-19 related epidemiological, pathophysiological and therapeutic problems, in order to manage at best the present emergency by appropriate protocols developed on the basis of the competences acquired and shared on the field. The aim of this document is to propose algorithms for the management of cardiovascular diseases during COVID-19 emergency with the objective of providing patients with optimal care, minimizing contagion risk and appropriately managing personal protective equipment.
- Published
- 2020
22. Automated analysis of pen-on-paper spirals for tremor detection, quantification, and differentiation.
- Author
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Rajan, Roopa, Anandapadmanabhan, Reghu, Nageswaran, Sharmila, Radhakrishnan, Vineeth, Saini, Arti, Krishnan, Syam, Gupta, Anu, Vishnu, Venugopalan Y., Pandit, Awadh K., Singh, Rajesh Kumar, Radhakrishnan, Divya M, Singh, Mamta Bhushan, Bhatia, Rohit, Srivastava, Achal, Kishore, Asha, and Padma Srivastava, M. V.
- Subjects
STATISTICS ,RESEARCH ,CONFIDENCE intervals ,ANALYSIS of variance ,TASK performance ,HANDWRITING ,ACCELEROMETERS ,DYSTONIA ,MOVEMENT disorders ,TREMOR ,DRAWING ,DESCRIPTIVE statistics ,PARKINSON'S disease ,SENSITIVITY & specificity (Statistics) ,DATA analysis ,RECEIVER operating characteristic curves ,DATA analysis software ,ALGORITHMS - Abstract
OBJECTIVE: To develop an automated algorithm to detect, quantify, and differentiate between tremor using pen-on-paper spirals. METHODS: Patients with essential tremor (n = 25), dystonic tremor (n = 25), Parkinson’s disease (n = 25), and healthy volunteers (HV, n = 25) drew free-hand spirals. The algorithm derived the mean deviation (MD) and tremor variability from scanned images. MD and tremor variability were compared with 1) the Bain and Findley scale, 2) the Fahn–Tolosa–Marin tremor rating scale (FTM–TRS), and 3) the peak power and total power of the accelerometer spectra. Inter and intra loop widths were computed to differentiate between the tremor. RESULTS: MD was higher in the tremor group (48.9±26.3) than in HV (26.4±5.3; p < 0.001). The cut-off value of 30.3 had 80.9% sensitivity and 76.0% specificity for the detection of the tremor [area under the curve: 0.83; 95% confidence index (CI): 0.75, 0.91, p < 0.001]. MD correlated with the Bain and Findley ratings (rho = 0.491, p = 0 < 0.001), FTM–TRS part B (rho = 0.260, p = 0.032) and accelerometric measures of postural tremor (total power, rho = 0.366, p < 0.001; peak power, rho = 0.402, p < 0.001). Minimum Detectable Change was 19.9%. Inter loop width distinguished Parkinson’s disease spirals from dystonic tremor (p < 0.001, 95% CI: 54.6, 211.1), essential tremor (p = 0.003, 95% CI: 28.5, 184.9), or HV (p = 0.036, 95% CI: -160.4, -3.9). CONCLUSION: The automated analysis of pen-on-paper spirals generated robust variables to quantify the tremor and putative variables to distinguish them from each other. SIGNIFICANCE: This technique maybe useful for epidemiological surveys and follow-up studies on tremor. [ABSTRACT FROM AUTHOR]
- Published
- 2023
- Full Text
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23. Management of Incidental Adnexal Findings on CT and MRI: A White Paper of the ACR Incidental Findings Committee
- Author
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Mindy M. Horrow, Maitray D. Patel, Katherine E. Maturen, Lincoln L. Berland, Pari V. Pandharipande, Susan M. Ascher, Perry J. Pickhardt, Mindy Goldman, and Liina Poder
- Subjects
Incidental Findings ,medicine.medical_specialty ,Ovarian cyst ,business.industry ,Patient characteristics ,medicine.disease ,Subspecialty ,Magnetic Resonance Imaging ,White paper ,Adnexal Diseases ,Expert opinion ,Abdomen ,medicine ,Humans ,Female ,Radiology, Nuclear Medicine and imaging ,Medical physics ,Quality of care ,Tomography, X-Ray Computed ,business ,Algorithms - Abstract
The ACR Incidental Findings Committee (IFC) presents recommendations for managing adnexal masses incidentally detected on CT and MRI. These recommendations represent an update of those provided in our previous JACR 2013 white paper. The Adnexal Subcommittee, which included six radiologists with subspecialty expertise in abdominal imaging or ultrasound and one gynecologist, developed this algorithm. The recommendations draw from published evidence and expert opinion and were finalized by iterative consensus. Algorithm branches successively categorize adnexal masses based on patient characteristics (eg, pre- versus postmenopausal) and imaging features. They terminate with a management recommendation. The algorithm addresses most, but not all, pathologies and clinical scenarios. Our goal is to improve quality of care by providing guidance on how to manage incidentally detected adnexal masses.
- Published
- 2020
24. 基于多目标优化的联邦学习进化.
- Author
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胡智勇, 于千城, 王之赐, and 张丽丝
- Subjects
FEDERATED learning ,ALGORITHMS ,PRIVACY - Abstract
Copyright of Application Research of Computers / Jisuanji Yingyong Yanjiu is the property of Application Research of Computers Edition and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
- Published
- 2024
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- View/download PDF
25. Classification of forensic hyperspectral paper data using hybrid spectral similarity algorithms.
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Devassy, Binu Melit, George, Sony, Nussbaum, Peter, and Thomas, Tessamma
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SPECTRAL imaging ,FORGERY ,ALGORITHMS ,FORENSIC sciences ,CLASSIFICATION ,CONFIDENCE intervals ,CLASSIFICATION algorithms - Abstract
Document forgeries that involve modification of the materials used, such as ink and paper, provide evidence of any malpractices being performed. Forensic specialists use different techniques to identify and classify these samples; however, the most preferred method is to use nondestructive techniques to avoid any potential damage to the original specimen under investigation. Hyperspectral imaging has already been explored in several application domains and used as a powerful method in forensic investigations to extract information about the materials under examination. To precisely classify the material information and utilize the hyperspectral imaging technique's potential, we probed the potential of some hybrid spectral similarity measures to classify different commonly used paper samples. A comparison of these methods is quantitatively presented in this article. Hybrid spectral similarity algorithms are tested on forensic analysis of paper data. We compared the classification capabilities of various hybrid spectral similarity algorithms on hyperspectral data of 40 different paper samples. The overall accuracy (OA), kappa K̂, Z‐score of kappa (ZK̂), and the 95% confidence interval of kappa (CI(K̂)) are used for comparison. The SID‐SAM and SID‐SCA produced an overall accuracy of 88% and 87%, respectively, which is highest among the hybrid spectral similarity measures tested. [ABSTRACT FROM AUTHOR]
- Published
- 2022
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26. Numerical simulations of paper-based electrophoretic separations with open-source tools
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Santiago Marquez Damian, Federico Schaumburg, Nicolas Franck, Gabriel Gerlero, and Pablo A. Kler
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Finite volume method ,Computer science ,010401 analytical chemistry ,Clinical Biochemistry ,Microfluidics ,02 engineering and technology ,Paper based ,Models, Theoretical ,021001 nanoscience & nanotechnology ,Supercomputer ,01 natural sciences ,Biochemistry ,Toolbox ,0104 chemical sciences ,Analytical Chemistry ,Image (mathematics) ,Computational science ,Open source ,Lab-On-A-Chip Devices ,Compatibility (mechanics) ,0210 nano-technology ,Algorithms ,Software - Abstract
A new tool for the solution of electromigrative separations in paper-based microfluidics devices is presented. The implementation is based on a recently published complete mathematical model for describing these types of separations, and was developed on top of the open-source toolbox electroMicroTransport, based on OpenFOAM® , inheriting all its features as native 3D problem handling, support for parallel computation, and a GNU GPL license . The presented tool includes full support for paper-based electromigrative separations (including EOF and the novel mechanical and electrical dispersion effects), compatibility with a well-recognized electrolyte database, and a novel algorithm for computing and controlling the electric current in arbitrary geometries. Additionally, the installation on any operating system is available due to its novel installation option in the form of a Docker image. A validation example with data from literature is included, and two extra application examples are provided, including a 2D free-flow IEF problem, which demonstrates the capabilities of the toolbox for dealing with computational and physicochemical modeling challenges simultaneously. This tool will enable efficient and reliable numerical prototypes of paper-based electrophoretic devices to accompany the contemporary fast growth in paper-based microfluidics.
- Published
- 2021
27. Selected Papers of the 32nd International Workshop on Combinatorial Algorithms, IWOCA 2021.
- Author
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Flocchini, Paola and Moura, Lucia
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EULERIAN graphs ,ALGORITHMS ,APPROXIMATION algorithms ,WEB hosting - Abstract
They give fixed parameter tractable algorithms for the problem parameterized by various structural parameters. The authors give a greedy loop-free algorithm for the exhaustive generation, a successor algorithm that runs in constant amortized time, among other algorithms, as well as results for the fixed spin generalization of this problem. IWOCA (International Workshop on Combinatorial Algorithms) is an annual conference series covering all aspects of combinatorial algorithms. [Extracted from the article]
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- 2023
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28. A review paper of optimal resource allocation algorithm in cloud environment.
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Patadiya, Namrata and Bhatt, Nirav
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RESOURCE allocation ,LITERATURE reviews ,SERVICE level agreements ,ALGORITHMS ,ELECTRONIC data processing ,CLOUD computing - Abstract
Cloud computing has become a popular approach for processing data and running computationally expensive services on a pay-as-you-go basis. Due to the ever-increasing requirement for cloud-based apps, appropriately allocating resources according to user requests while meeting service-level agreements between customers and service providers has become increasingly complex. An efficient and versatile resource allocation method is required to properly deploy these assets and meet user needs. The technique of distributing resources has become more arduous as user demand has increased. One of the key areas of research experts is how to design optimal solutions for this approach. In this paper, a literature review on proposed dynamic resource allocation approaches is introduced. [ABSTRACT FROM AUTHOR]
- Published
- 2023
- Full Text
- View/download PDF
29. MIRSIG position paper: the use of image registration and fusion algorithms in radiotherapy
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Nicholas, Lowther, Rob, Louwe, Johnson, Yuen, Nicholas, Hardcastle, Adam, Yeo, and Michael, Jameson
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Radiological and Ultrasound Technology ,Radiotherapy Planning, Computer-Assisted ,Image Processing, Computer-Assisted ,Biomedical Engineering ,Biophysics ,Humans ,Radiotherapy Dosage ,Radiology, Nuclear Medicine and imaging ,Instrumentation ,Algorithms ,Biotechnology - Abstract
The report of the American Association of Physicists in Medicine (AAPM) Task Group No. 132 published in 2017 reviewed rigid image registration and deformable image registration (DIR) approaches and solutions to provide recommendations for quality assurance and quality control of clinical image registration and fusion techniques in radiotherapy. However, that report did not include the use of DIR for advanced applications such as dose warping or warping of other matrices of interest. Considering that DIR warping tools are now readily available, discussions were hosted by the Medical Image Registration Special Interest Group (MIRSIG) of the Australasian College of Physical Scientists & Engineers in Medicine in 2018 to form a consensus on best practice guidelines. This position statement authored by MIRSIG endorses the recommendations of the report of AAPM task group 132 and expands on the best practice advice from the ‘Deforming to Best Practice’ MIRSIG publication to provide guidelines on the use of DIR for advanced applications.
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- 2022
30. Society of Skeletal Radiology– white paper. Guidelines for the diagnostic management of incidental solitary bone lesions on CT and MRI in adults: bone reporting and data system (Bone-RADS)
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Connie Y. Chang, Hillary W. Garner, Shivani Ahlawat, Behrang Amini, Matthew D. Bucknor, Jonathan A. Flug, Iman Khodarahmi, Michael E. Mulligan, Jeffrey J. Peterson, Geoffrey M. Riley, Mohammad Samim, Santiago A. Lozano-Calderon, and Jim S. Wu
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Adult ,Humans ,Radiology, Nuclear Medicine and imaging ,Radiology ,Tomography, X-Ray Computed ,Magnetic Resonance Imaging ,Algorithms - Abstract
The purpose of this article is to present algorithms for the diagnostic management of solitary bone lesions incidentally encountered on computed tomography (CT) and magnetic resonance (MRI) in adults. Based on review of the current literature and expert opinion, the Practice Guidelines and Technical Standards Committee of the Society of Skeletal Radiology (SSR) proposes a bone reporting and data system (Bone-RADS) for incidentally encountered solitary bone lesions on CT and MRI with four possible diagnostic management recommendations (Bone-RADS1, leave alone; Bone-RADS2, perform different imaging modality; Bone-RADS3, perform follow-up imaging; Bone-RADS4, biopsy and/or oncologic referral). Two algorithms for CT based on lesion density (lucent or sclerotic/mixed) and two for MRI allow the user to arrive at a specific Bone-RADS management recommendation. Representative cases are provided to illustrate the usability of the algorithms.
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- 2022
31. Computerized automated algorithm-based analyses of digitized paper ECGs in Brugada syndrome
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Antoine Leenhardt, Pierre Maison-Blanche, Isabelle Denjoy, Fabio Badilini, Pierre-Léo Laporte, Fabrice Extramiana, and Martino Vaglio
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Adult ,Male ,Acute effects ,medicine.medical_specialty ,Sudden death ,Electrocardiography ,QRS complex ,Internal medicine ,medicine ,Humans ,Repolarization ,cardiovascular diseases ,Brugada Syndrome ,Brugada syndrome ,business.industry ,Class I antiarrhythmic drug ,Middle Aged ,medicine.disease ,Increased risk ,Automated algorithm ,Cardiology ,Female ,Cardiology and Cardiovascular Medicine ,business ,Anti-Arrhythmia Agents ,Algorithms ,Software - Abstract
Background Brugada syndrome is a rare inherited arrhythmic syndrome with a coved type 1 ST-segment elevation on ECG and an increased risk of sudden death. Many studies have evaluated risk stratification performance based on ECG-derived parameters. However, since historical Brugada patient cohorts included mostly paper ECGs, most studies have been based on manual ECG parameter measurements. We hypothesized that it would be possible to run automated algorithm-based analysis of paper ECGs. We aimed: 1) to validate the digitization process for paper ECGs in Brugada patients; and 2) to quantify the acute class I antiarrhythmic drug effect on relevant ECG parameters in Brugada syndrome. Methods A total of 176 patients (30% female, 43 ± 13 years old) with induced type 1 Brugada syndrome ECG were included in the study. All of the patients had paper ECGs before and during class I antiarrhythmic drug challenge. Twenty patients also had a digital ECG, in whom printouts were used to validate the digitization process. Paper ECGs were scanned and then digitized using ECGScan software, version 3.4.0 (AMPS, LLC, New York, NY, USA) to obtain FDA HL7 XML format ECGs. Measurements were automatically performed using the Bravo (AMPS, LLC, New York, NY, USA) and Glasgow algorithms. Results ECG parameters obtained from digital and digitized ECGs were closely correlated (r = 0.96 ± 0.07, R2 = 0.93 ± 0.12). Class I antiarrhythmic drugs significantly increased the global QRS duration (from 113 ± 20 to 138 ± 23, p Conclusions Automated algorithm-based measurements of depolarization and repolarization parameters from digitized paper ECGs are reliable and could quantify the acute effects of class 1 antiarrhythmic drug challenge in Brugada patients. Our results support using computerized automated algorithm-based analyses from digitized paper ECGs to establish risk stratification decision trees in Brugada syndrome.
- Published
- 2021
32. Robust authentication for paper-based text documents based on text watermarking technology
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Zong Ming Guo, Tong Zhang, Yuxin Liu, Xi Feng Fang, Wei Guo, and Wen Fa Qi
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Scheme (programming language) ,Computer science ,Data_MISCELLANEOUS ,02 engineering and technology ,Pattern Recognition, Automated ,Image (mathematics) ,0502 economics and business ,Computer Graphics ,0202 electrical engineering, electronic engineering, information engineering ,Digital watermarking ,Computer Security ,Language ,computer.programming_language ,Authentication ,Information retrieval ,Content integrity ,Applied Mathematics ,05 social sciences ,Watermark ,General Medicine ,Paper based ,Data Compression ,Computational Mathematics ,Nonlinear Dynamics ,Modeling and Simulation ,ComputingMethodologies_DOCUMENTANDTEXTPROCESSING ,Embedding ,020201 artificial intelligence & image processing ,General Agricultural and Biological Sciences ,computer ,Algorithms ,Medical Informatics ,Software ,050203 business & management - Abstract
Aiming at the problem of easy tampering and difficult integrity authentication of paper text documents, this paper proposes a robust content authentication method for printed documents based on text watermarking scheme resisting print-and-scan attack. Firstly, an authentication watermark signal sequence related to content of text document is generated based on the Logistic chaotic map model; then, the authentication watermark signal sequence is embedded into printed paper document by using a robust text watermarking scheme; finally, the watermark information is extracted from scanned image of paper document, and compared with the authentication watermark information calculated in real time by the text document content obtained by OCR technology, thereby performing content integrity authentication of the paper text documents. Experimental results show that our method can achieve the robust content integrity authentication of paper text documents, and can also accurately locate the tampering position. In addition, the document after embedding the watermark information has a good visual effect, and the text watermarking scheme has a large information capacity.
- Published
- 2019
33. Paper-based 3D printing of anthropomorphic CT phantoms: Feasibility of two construction techniques
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Bernd Hamm, Marco Ziegert, Michael Scheel, Paul Jahnke, Felix Benjamin Schwarz, and Stephan Schwarz
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medicine.medical_specialty ,Image quality ,3D printing ,Iterative reconstruction ,Imaging phantom ,030218 nuclear medicine & medical imaging ,03 medical and health sciences ,0302 clinical medicine ,medicine ,Humans ,Radiology, Nuclear Medicine and imaging ,Projection (set theory) ,Radon transform ,Phantoms, Imaging ,business.industry ,General Medicine ,Paper based ,Sample (graphics) ,030220 oncology & carcinogenesis ,Printing, Three-Dimensional ,Feasibility Studies ,Radiographic Image Interpretation, Computer-Assisted ,Radiology ,Artifacts ,Tomography, X-Ray Computed ,business ,Head ,Algorithms ,Biomedical engineering - Abstract
To develop and evaluate methods for assembling radiopaque printed paper sheets to realistic patient phantoms for CT dose and image quality testing. CT images of two patients were radiopaque printed with aqueous potassium iodide solution (0.6 g/ml) on paper. Two methods were developed for assembling the paper sheets to head and neck phantoms. (1) Printed sheets were fed to a paper-based 3D printer along with corresponding 3D printable STL files. (2) Paper stacks of 5-mm thickness were glued with toner, cut to the patient shape and assembled to a phantom. In a sample application study, both phantoms were examined with five different tube current settings. Images were reconstructed using filtered-back projection (FBP) and iterative reconstruction (AIDR 3D) with three strength levels. Dose length product (DLP), signal-to-noise ratios (SNR) and contrast-to-noise ratios (CNRs) were analysed. Data were analysed using 2-way analysis of variance (ANOVA). Both methods achieved anthropomorphic phantoms with detailed patient anatomy. The 3D printer yielded a precise reproduction of the external patient shape, but caused visible glue artefacts. Gluing with toner avoided these artefacts and yielded more flexibility with regard to phantom size. In the sample application study, non-inferior SNR and CNR and up to 83.7% lower DLP were achieved on the phantoms with AIDR 3D compared with FBP. Two methods for assembling radiopaque printed paper sheets to phantoms of individual patients are presented. The sample application demonstrates potential for simulation of patient imaging and systematic CT dose and image quality assessment. • Two methods were developed to create realistic CT phantoms of individual patients from radiopaque printed paper sheets. • Analysis of five tube current and four reconstruction settings on two radiopaque 3D printed patient phantoms yielded non-inferior SNR and CNR and up to 83.7% lower dose with iterative reconstruction in comparison with filtered back projection. • Radiopaque 3D printed phantoms can simulate patients and allow systematic analysis of CT dose and image quality parameters.
- Published
- 2018
34. Hybrid Methods of Bibliographic Coupling and Text Similarity Measurement for Biomedical Paper Recommendation
- Author
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Hongmei, Guo, Zhesi, Shen, Jianxun, Zeng, and Na, Hong
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Cluster Analysis ,Algorithms - Abstract
The amount of available scientific literature is increasing, and studies have proposed various methods for evaluating document-document similarity in order to cluster or classify documents for science mapping and knowledge discovery. In this paper, we propose hybrid methods for bibliographic coupling (BC) and linear evaluation of text or content similarity: We combined BC with BM25, Cosine, and PMRA to compare their performances with single methods in paper recommendation tasks using TREC Genomics Track 2005datasets. For paper recommendation, BC and text-based methods complement each other, and hybrid methods were better than single methods. The combinations of BC with BM25 and BC with Cosine performed better than BC with PMRA. The performances were best when the weights of BM25, Cosine, and PMRA were 0.025, 0.2, and 0.2, respectively, in hybrid methods. For paper recommendation, the combinations of BC with text-based methods were better than BC or text-based methods used alone. The choice of method should depend on the actual data and research needs. In the future, the underlying reasons for the differences in performance and the specific part or type of information they complement in text clustering or recommendation need to be examined.
- Published
- 2022
35. The influence of memory, sample size effects, and filter paper material on online laser-based plant and soil water isotope measurements.
- Author
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Cui, Jiangpeng, Tian, Lide, Gerlein‐Safdi, Cynthia, and Qu, Dongmei
- Subjects
ISOTOPES ,INFRARED spectroscopy ,CAVITY-ringdown spectroscopy ,ALGORITHMS ,FILTER paper - Abstract
Rationale The recent development of isotope ratio infrared spectroscopy (IRIS) was quickly followed by the addition of online extraction and analysis systems, making it faster and easier to measure soil and plant water isotopes. However, memory and sample size effects limit the efficiency and accuracy of these new setups. In response, this study presents a scheme dedicated to estimating and eliminating these two effects. Methods Memory effect was determined by injecting two standard waters alternately. Each standard was injected nine times in a row and analyzed using induction module cavity ring-down spectroscopy (IM-CRDS). Memory coefficients were calculated using a new 'multistage jump' algorithm. Sample size effects were evaluated by injecting water volumes ranging from 1 μL to 6 μL. Finally, the influence of cellulose filter paper on the isotopic measurements, the memory, and the sample size effect was evaluated by comparing it with glass filter paper. Results Memory effects were detected for both δ
18 O and δ2 H values, with the latter being stronger. Isotopic differences between replicates of the same plant or soil sample showed a clear decrease after memory correction. A small water volume effect was found only when the injected water volume was larger than 3 μL. However, while the correction method performed well for laboratory-made samples, it did not for field samples, due to the heterogeneity of the isotopic composition of the samples. Stronger memory and water volume effects were found for cellulose filter paper. Conclusions The memory coefficients and the water volume-isotope relationship improved the consistency and accuracy of both laboratory and field data. Our results indicate that cellulose filter paper may not be a suitable medium to measure standard waters and evaluate memory and water volume effects. Finally, a detailed correction and calibration protocol is suggested, along with notes on best practices to obtain good-quality IM-CRDS data. Copyright © 2017 John Wiley & Sons, Ltd. [ABSTRACT FROM AUTHOR]- Published
- 2017
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36. Development and Validation of an Algorithm for the Digitization of ECG Paper Images.
- Author
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Randazzo, Vincenzo, Puleo, Edoardo, Paviglianiti, Annunziata, Vallan, Alberto, and Pasero, Eros
- Subjects
DIGITIZATION ,DIGITAL images ,ELECTROCARDIOGRAPHY ,HEART rate monitors ,PEARSON correlation (Statistics) ,MEASUREMENT errors ,HEART beat ,ALGORITHMS - Abstract
The electrocardiogram (ECG) signal describes the heart's electrical activity, allowing it to detect several health conditions, including cardiac system abnormalities and dysfunctions. Nowadays, most patient medical records are still paper-based, especially those made in past decades. The importance of collecting digitized ECGs is twofold: firstly, all medical applications can be easily implemented with an engineering approach if the ECGs are treated as signals; secondly, paper ECGs can deteriorate over time, therefore a correct evaluation of the patient's clinical evolution is not always guaranteed. The goal of this paper is the realization of an automatic conversion algorithm from paper-based ECGs (images) to digital ECG signals. The algorithm involves a digitization process tested on an image set of 16 subjects, also with pathologies. The quantitative analysis of the digitization method is carried out by evaluating the repeatability and reproducibility of the algorithm. The digitization accuracy is evaluated both on the entire signal and on six ECG time parameters (R-R peak distance, QRS complex duration, QT interval, PQ interval, P-wave duration, and heart rate). Results demonstrate the algorithm efficiency has an average Pearson correlation coefficient of 0.94 and measurement errors of the ECG time parameters are always less than 1 mm. Due to the promising experimental results, the algorithm could be embedded into a graphical interface, becoming a measurement and collection tool for cardiologists. [ABSTRACT FROM AUTHOR]
- Published
- 2022
- Full Text
- View/download PDF
37. LA INTEL·LIGÈNCIA ARTIFICIAL EN LA DETECCIÓ DE LES PRÀCTIQUES DE BID RIGGING: EL PAPER CAPDAVANTER DE L'ACCO.
- Author
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Jiménez Cardona, Noemí
- Subjects
GOVERNMENT purchasing ,ARTIFICIAL intelligence ,ANTITRUST law ,SOFTWARE development tools ,CARTELS - Abstract
Copyright of Revista Catalana de Dret Públic is the property of Revista Catalana de Dret Public and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
- Published
- 2022
- Full Text
- View/download PDF
38. Letter on the results of the BASiNET method in the paper 'A systematic evaluation of computational tools for lncRNA identification'
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Fabrício Martins Lopes and Matheus H Pimenta-Zanon
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Computational Biology ,RNA, Long Noncoding ,Molecular Biology ,Algorithms ,Information Systems - Abstract
This letter points out a conceptual error made by the authors of a published paper, which presents a review and evaluation of computational methods in lncRNA identification. The error was made in the execution of the BASiNET method when considering an example file (toy model) made available by the authors with the aim of showing how a classification model could be stored in a file for later use. In this letter, this error is contextualized, the correct use of the BASiNET method is pointed out and the results of its correct execution to one of the datasets used in the review article are presented. The results clearly show the misuse of the method and present its correct use so that it can be fairly compared with other methods in the literature and prevent its misuse from being replicated by new studies.
- Published
- 2022
39. 'Re-Materialized' Medical Data: Paper-Based Transmission of Structured Medical Data Using QR-Code, for Medical Imaging Reports
- Author
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Arthur, Lauriot Dit Prevost, Raphaël, Bentegeac, Audrey, Dequesnes, Adrien, Billiau, Emmanuel, Baudelet, Rémi, Legleye, Marc-Antoine, Hubaut, Michel, Cassagnou, Philippe, Puech, Rémi, Besson, and Emmanuel, Chazard
- Subjects
Diagnostic Imaging ,Radiography ,Information Storage and Retrieval ,Smartphone ,Algorithms - Abstract
Although paper-based transmission of medical information might seem outdated, it has proven efficient, and remains structurally safe from massive data leaks. As part of the ICIPEMIR project for improving medical imaging report, we explored the idea of structured data storage within a medical report, by embedding the data themselves in a QR-Code (and no URL-to-the-data). Three different datasets from ICIPEMIR were serialized, then encoded in a QR-Code. We compared 4 compression algorithms to reduce file size before QR-Encoding. YAML was the most concise format (character sparing), and allowed for embedding of a 2633-character serialized file within a QR-Code. The best compression rate was obtained with gzip, with a compression ratio of 2.32 in 15.7ms. Data were easily extracted and decompressed from a digital QR-Code using a simple command line. YAML file was also successfully recovered from the printed QR-Code with both Android and iOS smartphone. Minimal detected size was 3*3cm.
- Published
- 2022
40. Social and content aware One-Class recommendation of papers in scientific social networks.
- Author
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Wang, Gang, He, XiRan, and Ishuga, Carolyne Isigi
- Subjects
INFORMATION technology ,SOCIAL networks ,SPARSE graphs ,HYBRID computers (Computer architecture) ,HYBRID power systems - Abstract
With the rapid development of information technology, scientific social networks (SSNs) have become the fastest and most convenient way for researchers to communicate with each other. Many published papers are shared via SSNs every day, resulting in the problem of information overload. How to appropriately recommend personalized and highly valuable papers for researchers is becoming more urgent. However, when recommending papers in SSNs, only a small amount of positive instances are available, leaving a vast amount of unlabelled data, in which negative instances and potential unseen positive instances are mixed together, which naturally belongs to One-Class Collaborative Filtering (OCCF) problem. Therefore, considering the extreme data imbalance and data sparsity of this OCCF problem, a hybrid approach of Social and Content aware One-class Recommendation of Papers in SSNs, termed SCORP, is proposed in this study. Unlike previous approaches recommended to address the OCCF problem, social information, which has been proved playing a significant role in performing recommendations in many domains, is applied in both the profiling of content-based filtering and the collaborative filtering to achieve superior recommendations. To verify the effectiveness of the proposed SCORP approach, a real-life dataset from CiteULike was employed. The experimental results demonstrate that the proposed approach is superior to all of the compared approaches, thus providing a more effective method for recommending papers in SSNs. [ABSTRACT FROM AUTHOR]
- Published
- 2017
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41. Canadian Association of Radiologists White Paper on De-identification of Medical Imaging: Part 2, Practical Considerations
- Author
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Flavie Lavoie-Cardinal, Khaled El-Emam, Bruce Gray, Casey Hurrell, Caroline Reinhold, Mark Cicero, An Tang, Marleine Azar, William Parker, Jacob L. Jaremko, Lori Sheremeta, Emil Lee, Andrea Lum, Benoit Desjardins, and Rebecca Bromwich
- Subjects
Diagnostic Imaging ,Canada ,Knowledge management ,Best practice ,Data management ,Lifelong learning ,Big data ,030218 nuclear medicine & medical imaging ,Machine Learning ,03 medical and health sciences ,0302 clinical medicine ,White paper ,Artificial Intelligence ,Data Anonymization ,Health care ,Radiologists ,Medicine ,Humans ,Radiology, Nuclear Medicine and imaging ,Societies, Medical ,business.industry ,De-identification ,General Medicine ,Data sharing ,030220 oncology & carcinogenesis ,business ,Algorithms - Abstract
The application of big data, radiomics, machine learning, and artificial intelligence (AI) algorithms in radiology requires access to large data sets containing personal health information. Because machine learning projects often require collaboration between different sites or data transfer to a third party, precautions are required to safeguard patient privacy. Safety measures are required to prevent inadvertent access to and transfer of identifiable information. The Canadian Association of Radiologists (CAR) is the national voice of radiology committed to promoting the highest standards in patient-centered imaging, lifelong learning, and research. The CAR has created an AI Ethical and Legal standing committee with the mandate to guide the medical imaging community in terms of best practices in data management, access to health care data, de-identification, and accountability practices. Part 2 of this article will inform CAR members on the practical aspects of medical imaging de-identification, strengths and limitations of de-identification approaches, list of de-identification software and tools available, and perspectives on future directions.
- Published
- 2020
42. Paper currency defect detection algorithm using quaternion uniform strength.
- Author
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Gai, Shan, Xu, Xiaolin, and Xiong, Bangshu
- Subjects
ALGORITHMS ,QUATERNIONS ,MONEY ,IMAGE registration ,MATHEMATICAL convolutions - Abstract
In this paper, we propose a novel paper currency defect detection algorithm using quaternion uniform strength. We first build paper currency image preprocessing integration framework which includes intensity balancing, paper currency location, and geometric correction. We then propose a global–local paper currency image registration algorithm by moving key areas within certain range which can eliminate the false difference effectively. Finally, the quaternion uniform strength is calculated by using quaternion convolution edge detector. The defect degree of paper currency is determined by using the quaternion uniform color difference. The proposed algorithm is tested using different datasets from five countries: CNY, USD, EUR, VND, and RUB. The experimental results demonstrate that the proposed algorithm yields better results than the existing state-of-the-art paper currency defect detection techniques. The demo of the proposed paper currency defect detection algorithm will be publicly available. [ABSTRACT FROM AUTHOR]
- Published
- 2020
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- View/download PDF
43. The management of unanticipated difficult airways in children of all age groups in anaesthetic practice - the position paper of an expert panel
- Author
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Zenon Halaba, Dawid Aleksandrowicz, Marek Migdał, Tomasz Gaszyński, Wojciech Walas, Andrzej Piotrowski, Ewa Helwich, Grażyna Siejka, Maria K Kornacka, Alicja Bartkowska-Śniatkowska, and Tomasz Szczapa
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medicine.medical_specialty ,Critical Care ,medicine.medical_treatment ,Difficult intubation ,Guideline ,Critical Care and Intensive Care Medicine ,03 medical and health sciences ,0302 clinical medicine ,Neonate ,Age groups ,030202 anesthesiology ,Anesthesiology ,Intensive care ,Medicine ,Intubation ,Hypoxic brain injury ,Humans ,Airway Management ,Intensive care medicine ,Child ,Hypoxia ,Difficult airway ,Societies, Medical ,Unanticipated difficult airway ,business.industry ,lcsh:Medical emergencies. Critical care. Intensive care. First aid ,Infant ,lcsh:RC86-88.9 ,Emergency situations ,Emergency Medicine ,Position paper ,Child and adolescent ,business ,030217 neurology & neurosurgery ,Algorithms - Abstract
Children form a specific group of patients, as there are significant differences between children and adults in both anatomy and physiology. Difficult airway may be unanticipated or anticipated. Difficulties encountered during intubation may cause hypoxia, hypoxic brain injury and, in extreme situations, may result in the patient’s death. There are few paediatric difficult-airway guidelines available in the current literature, and some of these have significant limitations. This position paper, intended for unanticipated difficult airway, was elaborated by the panel of specialists representing the Polish Society of Anaesthesiology and Intensive Care as well as the Polish Neonatal Society. It covers both elective intubation and emergency situations in children in all age groups. An integral part of the paper is an algorithm. The paper describes in detail all stages of the algorithm considering some modification in specific age groups, i.e. neonates.
- Published
- 2019
44. Paper-based 3D printing of anthropomorphic CT phantoms: Feasibility of two construction techniques.
- Author
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Jahnke, Paul, Schwarz, Stephan, Ziegert, Marco, Schwarz, Felix Benjamin, Hamm, Bernd, and Scheel, Michael
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ALGORITHMS ,COMPUTED tomography ,DIAGNOSTIC imaging ,HEAD ,COMPUTERS in medicine ,IMAGING phantoms ,RESEARCH funding ,PILOT projects ,THREE-dimensional printing ,MEDICAL artifacts - Abstract
Objectives: To develop and evaluate methods for assembling radiopaque printed paper sheets to realistic patient phantoms for CT dose and image quality testing.Methods: CT images of two patients were radiopaque printed with aqueous potassium iodide solution (0.6 g/ml) on paper. Two methods were developed for assembling the paper sheets to head and neck phantoms. (1) Printed sheets were fed to a paper-based 3D printer along with corresponding 3D printable STL files. (2) Paper stacks of 5-mm thickness were glued with toner, cut to the patient shape and assembled to a phantom. In a sample application study, both phantoms were examined with five different tube current settings. Images were reconstructed using filtered-back projection (FBP) and iterative reconstruction (AIDR 3D) with three strength levels. Dose length product (DLP), signal-to-noise ratios (SNR) and contrast-to-noise ratios (CNRs) were analysed. Data were analysed using 2-way analysis of variance (ANOVA).Results: Both methods achieved anthropomorphic phantoms with detailed patient anatomy. The 3D printer yielded a precise reproduction of the external patient shape, but caused visible glue artefacts. Gluing with toner avoided these artefacts and yielded more flexibility with regard to phantom size. In the sample application study, non-inferior SNR and CNR and up to 83.7% lower DLP were achieved on the phantoms with AIDR 3D compared with FBP.Conclusions: Two methods for assembling radiopaque printed paper sheets to phantoms of individual patients are presented. The sample application demonstrates potential for simulation of patient imaging and systematic CT dose and image quality assessment.Key Points: • Two methods were developed to create realistic CT phantoms of individual patients from radiopaque printed paper sheets. • Analysis of five tube current and four reconstruction settings on two radiopaque 3D printed patient phantoms yielded non-inferior SNR and CNR and up to 83.7% lower dose with iterative reconstruction in comparison with filtered back projection. • Radiopaque 3D printed phantoms can simulate patients and allow systematic analysis of CT dose and image quality parameters. [ABSTRACT FROM AUTHOR]- Published
- 2019
- Full Text
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45. Combining Optical Character Recognition With Paper ECG Digitization
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Amit J. Shah, Srini Tridandapani, Pamela Bhatti, Shambavi Ganesh, Mhmtjamil Alkhalaf, and Shishir Gupta
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optical character recognition ,Computer science ,Computer applications to medicine. Medical informatics ,Biomedical Engineering ,R858-859.7 ,computer.software_genre ,Article ,connected component analysis ,Electrocardiography ,Cohen's kappa ,Medical technology ,Electronic Health Records ,Humans ,ComputerSystemsOrganization_SPECIAL-PURPOSEANDAPPLICATION-BASEDSYSTEMS ,Medical diagnosis ,R855-855.5 ,electronic medical record ,Digitization ,Graphical user interface ,business.industry ,Pattern recognition ,Signal Processing, Computer-Assisted ,General Medicine ,Optical character recognition ,Image segmentation ,Interfacing ,Artificial intelligence ,business ,computer ,Connected-component labeling ,Algorithms - Abstract
Objective: We propose a MATLAB-based tool to convert electrocardiography (ECG) waveforms from paper-based ECG records into digitized ECG signals that is vendor-agnostic. The tool is packaged as an open source standalone graphical user interface (GUI) based application. Methods and procedures: To reach this objective we: (1) preprocess the ECG records, which includes skew correction, background grid removal and linear filtering; (2) segment ECG signals using Connected Components Analysis (CCA); (3) implement Optical Character Recognition (OCR) for removal of overlapping ECG lead characters and for interfacing of patients’ demographic information with their research records or their electronic medical record (EMR). The ECG digitization results are validated through a reader study where clinically salient features, such as intervals of QRST complex, between the paper ECG records and the digitized ECG records are compared. Results: Comparison of clinically important features between the paper-based ECG records and the digitized ECG signals, reveals intra- and inter-observer correlations of 0.86–0.99 and 0.79–0.94, respectively. The kappa statistic was found to average at 0.86 and 0.72 for intra- and inter-observer correlations, respectively. Conclusion: The clinically salient features of the ECG waveforms such as the intervals of QRST complex, are preserved during the digitization procedure. Clinical and Healthcare Impact: This open-source digitization tool can be used as a research resource to digitize paper ECG records thereby enabling development of new prediction algorithms to risk stratify individuals with cardiovascular disease, and/or allow for development of ECG-based cardiovascular diagnoses relying upon automated digital algorithms.
- Published
- 2021
46. Reply to 'Describing center of pressure movement in stabilometry by ellipse area approximation' from Agnieszka Gołąb concerning the paper 'A Review of Center of Pressure (COP) Variables to Quantify Standing Balance in Elderly People: Algorithms and Open Access Code'
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Flavien, Quijoux and Alice, Nicolaï
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Access to Information ,Review Literature as Topic ,Movement ,Humans ,Postural Balance ,Algorithms ,Aged - Abstract
Letter to the Editor concerning "Describing center of pressure movement in stabilometry by ellipse area approximation" from Agnieszka Gołąb.
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- 2022
47. Utilizing tables, figures, charts and graphs to enhance the readability of a research paper.
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Divecha C. A., Tullu M. S., and Karande S.
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GRAPHIC arts ,READABILITY (Literary style) ,SERIAL publications ,RESEARCH methodology ,COPYRIGHT ,MEDICAL research ,ALGORITHMS - Abstract
The authors offer observation on utilizing tables, figures, charts and graphs to help understand the research presented in a simple manner but also engage and sustain the reader's interest. Topics discussed include benefits provided by the use of tables/figures/charts/graphs, general methodology of design and submission, and copyright issues of using material from government publications/public domain.
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- 2023
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48. Diagnosis and risk stratification of chest pain patients in the emergency department: focus on acute coronary syndromes. A position paper of the Acute Cardiovascular Care Association
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Maria Rubini Guimenez, Héctor Bueno, Janina Stępińska, Anna Oleksiak, Gregory Y.H. Lip, Christian Mueller, Doron Zahger, Elia De Maria, Roberta Petrino, Marc J. Claeys, Roberta Rossini, Thomas Muenzel, Abdo Khoury, Luis Garcia-Castrillo, Patrizio Lancellotti, Kurt Huber, Ingo Ahrens, Christiaan J M Vrints, Maddelena Lettino, and Sigrun Halvorsen
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Male ,medicine.medical_specialty ,Chest Pain ,Decision Making ,Cardiology ,Myocardial Infarction ,Cardiovascular care ,Critical Care and Intensive Care Medicine ,Chest pain ,Risk Assessment ,Percutaneous Coronary Intervention ,medicine ,Humans ,Myocardial infarction ,Acute Coronary Syndrome ,Societies, Medical ,biology ,business.industry ,General Medicine ,Emergency department ,Middle Aged ,medicine.disease ,Triage ,Troponin ,Patient Care Management ,Europe ,Emergency medicine ,Risk stratification ,Acute Disease ,biology.protein ,Position paper ,ST Elevation Myocardial Infarction ,Female ,Human medicine ,medicine.symptom ,Cardiology and Cardiovascular Medicine ,business ,Emergency Service, Hospital ,Algorithms ,Biomarkers - Abstract
This paper provides an update on the European Society of Cardiology task force report on the management of chest pain. Its main purpose is to provide an update on the decision algorithms and diagnostic pathways to be used in the emergency department for the assessment and triage of patients with chest pain symptoms suggestive of acute coronary syndromes.
- Published
- 2020
49. Artificial intelligence and breast screening: French Radiology Community position paper
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L Verzaux, B Séradour, A Maire, G Lenczner, Corinne Balleyguier, P Heid, Isabelle Thomassin-Naggara, Patrice Taourel, Luc Ceugnart, CHU Tenon [AP-HP], Sorbonne Université (SU)-Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP), Sorbonne Université (SU), and Hôpital Lapeyronie [Montpellier] (CHU)
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Digital mammography ,Breast imaging ,[SDV.IB.IMA]Life Sciences [q-bio]/Bioengineering/Imaging ,[SDV]Life Sciences [q-bio] ,Breast Neoplasms ,Radiation Dosage ,Digital breast tomosynthesis ,030218 nuclear medicine & medical imaging ,03 medical and health sciences ,Screening program ,0302 clinical medicine ,Breast cancer ,Artificial Intelligence ,medicine ,Image Processing, Computer-Assisted ,Breast screening ,Humans ,Radiology, Nuclear Medicine and imaging ,Precision Medicine ,Early Detection of Cancer ,Breast Density ,Radiological and Ultrasound Technology ,business.industry ,General Medicine ,medicine.disease ,3. Good health ,030220 oncology & carcinogenesis ,Related research ,Clinical value ,Position paper ,Female ,Breast disease ,Artificial intelligence ,France ,business ,Algorithms ,Needs Assessment ,Mammography - Abstract
International audience; The objective of this article was to evaluate the evidence currently available about the clinical value of artificial intelligence (AI) in breast imaging. Nine experts from the disciplines involved in breast disease management – including physicists and radiologists – convened a meeting on June 3, 2019 to discuss the evidence for the use of this technology in plenary and focused sessions. Prior to the meeting, the group performed a literature review on predefined topics. This paper presents the consensus reached by this working group on recommendations for the future use of AI in breast screening and related research topics.
- Published
- 2019
50. COAP 2019 Best Paper Prize: Paper of S. Gratton, C. W. Royer, L. N. Vicente, and Z. Zhang.
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APPLIED mathematics ,ALGORITHMS ,SCIENTIFIC computing ,PRIZES (Contests & competitions) ,ALGORITHMIC randomness - Abstract
Each year, the editorial board of Computational Optimization and Applications selects a paper from the preceding year's publications for the Best Paper Award. This derivative-free algorithm relies on randomly generated directions and is analyzed from a probabilistic viewpoint, leading to complexity guarantees for both deterministic and probabilistic versions of the method. First, following recent developments in nonconvex optimization, complexity results have become increasingly popular in derivative-free optimization [[8]]. [Extracted from the article]
- Published
- 2020
- Full Text
- View/download PDF
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