19 results on 'LN cat08778a'
Search Results
2. The Convergence of Human and Artificial Intelligence on Clinical Care - Part I.
- Author
-
Abedi, Vida and Abedi, Vida
- Subjects
Medicine ,machine learning-enabled decision support system ,improving diagnosis accuracy ,Bayesian network ,bariatric surgery ,health-related quality of life ,comorbidity ,voice change ,larynx cancer ,machine learning ,deep learning ,voice pathology classification ,imputation ,electronic health records ,EHR ,laboratory measures ,medical informatics ,inflammatory bowel disease ,C. difficile infection ,osteoarthritis ,complex diseases ,healthcare ,artificial intelligence ,interpretable machine learning ,explainable machine learning ,septic shock ,clinical decision support system ,electronic health record ,cerebrovascular disorders ,stroke ,SARS-CoV-2 ,COVID-19 ,cluster analysis ,risk factors ,ischemic stroke ,outcome prediction ,recurrent stroke ,cardiac ultrasound ,echocardiography ,portable ultrasound ,aneurysm surgery ,temporary artery occlusion ,clipping time ,artificial neural network ,digital imaging ,monocytes ,promonocytes and monoblasts ,chronic myelomonocytic leukemia (CMML) and acute myeloid leukemia (AML) for acute monoblastic leukemia and acute monocytic leukemia ,concordance between hematopathologists ,mechanical ventilation ,respiratory failure ,ADHD ,social media ,Twitter ,pharmacotherapy ,stimulants ,alpha-2-adrenergic agonists ,non-stimulants ,trust ,passive adherence ,human factors - Abstract
Summary: This edited book contains twelve studies, large and pilots, in five main categories: (i) adaptive imputation to increase the density of clinical data for improving downstream modeling; (ii) machine-learning-empowered diagnosis models; (iii) machine learning models for outcome prediction; (iv) innovative use of AI to improve our understanding of the public view; and (v) understanding of the attitude of providers in trusting insights from AI for complex cases. This collection is an excellent example of how technology can add value in healthcare settings and hints at some of the pressing challenges in the field. Artificial intelligence is gradually becoming a go-to technology in clinical care; therefore, it is important to work collaboratively and to shift from performance-driven outcomes to risk-sensitive model optimization, improved transparency, and better patient representation, to ensure more equitable healthcare for all.
3. Systems Radiology and Personalized Medicine.
- Author
-
de Jong, Pim A., Foppen, Wouter, Tolboom, Nelleke, and de Jong, Pim A.
- Subjects
Medicine ,COVID-19 ,chest X-ray ,deep learning ,convolutional neural network ,Grad-CAM ,computed tomography ,image analysis ,osteoarthritis ,reliability ,FDG-PET/CT ,infection ,bloodstream infection ,endocarditis ,vascular graft infection ,spondylodiscitis ,cyst infection ,white blood cell scintigraphy ,total body PET/CT ,radiotracers ,artificial intelligence ,contrast media ,body composition ,large vessel vasculitis ,atherosclerosis ,imaging ,FDG-PET ,radiological imaging ,MRI ,non-contrast ,venography ,TRANCE ,QFlow ,neuroblastoma ,nuclear medicine ,radionuclide imaging ,[123I]mIBG ,[124I]mIBG ,[18F]mFBG ,[18F]FDG ,[68Ga]Ga-DOTA peptides ,[18F]F-DOPA ,[11C]mHED ,chronic limb-threatening ischemia ,peripheral arterial disease ,calcification pattern ,diffuse idiopathic skeletal hyperostosis ,risk factors ,adiposity ,intra-abdominal fat ,cardiorenal syndrome ,imaging biomarker ,tissue characterization ,cerebral aneurysm ,computational fluid dynamics ,hemodynamic ,morphological ,rupture ,n/a - Abstract
Summary: Medicine has evolved into a high level of specialization using the very detailed imaging of organs. This has impressively solved a multitude of acute health-related problems linked to single-organ diseases. Many diseases and pathophysiological processes, however, involve more than one organ. An organ-based approach is challenging when considering disease prevention and caring for elderly patients, or those with systemic chronic diseases or multiple co-morbidities. In addition, medical imaging provides more than a pretty picture. Much of the data are now revealed by quantitating algorithms with or without artificial intelligence. This Special Issue on "Systems Radiology and Personalized Medicine" includes reviews and original studies that show the strengths and weaknesses of structural and functional whole-body imaging for personalized medicine.
4. Industry 4.0 for SMEs - Smart Manufacturing and Logistics for SMEs.
- Author
-
Rauch, Erwin, Woschank, Manuel, and Rauch, Erwin
- Subjects
History of engineering & technology ,latent semantic analysis ,virtual quality management ,concept investigation ,concept disambiguation ,knowledge discovery ,sustainable methodologies ,small and medium sized enterprises ,material handling systems ,simulation ,ARENA®, time study ,overall equipment effectiveness ,manufacturing performance ,Industry 4.0 ,manufacturing sustainability ,manufacturing process model ,business process management ,hierarchical clustering ,similarity ,BPMN ,human factors ,cyber-physical systems ,cyber-physical production systems ,anthropocentric design ,Operator 4.0 ,human-machine interaction ,energy efficient operation ,manufacturing system ,stochastic event ,digital twin ,Max-plus Algebra ,MATLAB-Simulink ,advanced manufacturing ,industry 4.0 ,SME ,technology adoption model ,assembly supply chain ,sustainability ,complexity indicators ,testing criteria ,SMEs ,e-business modelling ,LSP Lifecycle Model ,Quality Function Deployment ,Best-Worst Method ,Internet of Things ,India ,awareness ,small and medium-sized enterprises ,assessment model ,collaborative robotics ,physical ergonomics ,human-robot collaboration ,human-centered design ,assembly ,small and medium sized enterprise ,positive complexity ,negative complexity ,infeasible configurations ,product platform ,customer's perception ,assessment ,field study ,smart manufacturing ,cloud platform ,artificial intelligence ,machine learning ,deep learning ,smart logistics ,logistics 4.0 ,smart technologies ,sustainable agriculture ,plant factory - Abstract
Summary: In recent years, the industrial environment has been changing radically due to the introduction of concepts and technologies based on the fourth industrial revolution, also known as Industry 4.0. After the introduction of Industry 4.0 in large enterprises, SMEs have moved into the focus, as they are the backbone of many economies. Small organizations are increasingly proactive in improving their operational processes, which is a good starting point for introducing the new concepts of Industry 4.0. The readiness of SME-adapted Industry 4.0 concepts and the organizational capability of SMEs to meet this challenge exist only in some areas. This reveals the need for further research and action plans for preparing SMEs in a technical and organizational direction. Therefore, special research and investigations are needed for the implementation of Industry 4.0 technologies and concepts in SMEs. SMEs will only achieve Industry 4.0 by following SME-customized implementation strategies and approaches and realizing SME-adapted concepts and technological solutions. Thus, this Special Issue represents a collection of theoretical models as well as practical case studies related to the introduction of Industry 4.0 concepts in small- and medium-sized enterprises.
5. Swarms and Network Intelligence.
- Author
-
Altshuler, Yaniv, Pereira, Francisco Camara, David, Eli, and Altshuler, Yaniv
- Subjects
Information technology industries ,Computer science ,generative design ,automated learning ,evolutionary learning ,co-design ,genetic programming ,human behavior ,socioeconomic status ,data analysis ,social media ,crowd-sourcing ,wisdom of the crowd ,social learning ,Bayesian models ,risk ,Docker Swarm ,leader election ,privilege escalation ,defense evasion ,cloud ,collective intelligence ,crowdsourcing ,policymaking ,public policy ,e-participation ,literature review ,deep learning ,cybersecurity ,artificial intelligence ,swarm intelligence ,adversarial AI ,information theory ,entropy ,models ,neural networks ,communication ,multi-agent ,deep reinforcement learning ,partial observability ,distributed estimation ,Sparse Bayesian Learning ,exploration ,swarm ,multi-agent systems ,consensus ,D-optimal design ,mobile crowdsensing ,UAV control ,graph network ,maximum-entropy learning ,mobile robotics ,swarms ,crowd dynamics ,natural algorithms ,locusts ,n/a - Abstract
Summary: This reprint covers a wide range of topics related to collective intelligence, exploring the interplay between swarm intelligence, network intelligence, and other emerging technologies. The first set of chapters focuses on the behavior and mechanisms of swarming. One chapter describes a locust-inspired model of collective marching on rings, while another demonstrates the experimental validation of entropy-driven swarm exploration under sparsity constraints using sparse Bayesian learning. These studies provide new insights into the principles of swarming and its potential applications in fields such as robotics and mobile crowdsensing. The next set of chapters discusses the integration of swarm intelligence with other emerging technologies such as deep learning and graph theory. These studies show how swarm intelligence can be combined with other advanced technologies to solve complex problems and improve decision-making processes. The reprint also covers the topic of network intelligence, including the study of social network analysis, Twitter user activity, and crowd-sourced financial predictions. These studies provide insights into how network intelligence can be harnessed to understand social dynamics and improve decision-making processes in various domains. The reprint concludes with a chapter that proposes a generative design approach for the efficient mathematical modeling of complex systems.
6. Computational Optimizations for Machine Learning.
- Author
-
Gabbay, Freddy and Gabbay, Freddy
- Subjects
Research & information: general ,Mathematics & science ,ARIMA model ,time series analysis ,online optimization ,online model selection ,precipitation nowcasting ,deep learning ,autoencoders ,radar data ,generalization error ,recurrent neural networks ,machine learning ,model predictive control ,nonlinear systems ,neural networks ,low power ,quantization ,CNN architecture ,multi-objective optimization ,genetic algorithms ,evolutionary computation ,swarm intelligence ,Heating, Ventilation and Air Conditioning (HVAC) ,metaheuristics search ,bio-inspired algorithms ,smart building ,soft computing ,training ,evolution of weights ,artificial intelligence ,deep neural networks ,convolutional neural network ,deep compression ,DNN ,ReLU ,floating-point numbers ,hardware acceleration ,energy dissipation ,FLOW-3D ,hydraulic jumps ,bed roughness ,sensitivity analysis ,feature selection ,evolutionary algorithms ,nature inspired algorithms ,meta-heuristic optimization ,computational intelligence - Abstract
Summary: The present book contains the 10 articles finally accepted for publication in the Special Issue "Computational Optimizations for Machine Learning" of the MDPI journal Mathematics, which cover a wide range of topics connected to the theory and applications of machine learning, neural networks and artificial intelligence. These topics include, among others, various types of machine learning classes, such as supervised, unsupervised and reinforcement learning, deep neural networks, convolutional neural networks, GANs, decision trees, linear regression, SVM, K-means clustering, Q-learning, temporal difference, deep adversarial networks and more. It is hoped that the book will be interesting and useful to those developing mathematical algorithms and applications in the domain of artificial intelligence and machine learning as well as for those having the appropriate mathematical background and willing to become familiar with recent advances of machine learning computational optimization mathematics, which has nowadays permeated into almost all sectors of human life and activity.
7. Applied Neural Networks and Fuzzy Logic in Power Electronics, Motor Drives, Renewable Energy Systems and Smart Grids.
- Author
-
Simões, Marcelo Godoy, Paredes, Helmo Kelis Morales, and Simões, Marcelo Godoy
- Subjects
History of engineering & technology ,droop curve ,frequency regulation ,fuzzy logic ,the rate of change of frequency ,reserve power ,smart grid ,energy Internet ,convolutional neural network ,decision optimization ,deep reinforcement learning ,electric load forecasting ,non-dominated sorting genetic algorithm II ,multi-layer perceptron ,adaptive neuro-fuzzy inference system ,meta-heuristic algorithms ,automatic generation control ,fuzzy neural network control ,thermostatically controlled loads ,back propagation algorithm ,particle swarm optimization ,load disaggregation ,artificial intelligence ,cognitive meters ,machine learning ,state machine ,NILM ,non-technical losses ,semi-supervised learning ,knowledge embed ,deep learning ,distribution network equipment ,condition assessment ,multi information source ,fuzzy iteration ,current balancing algorithm ,level-shifted SPWM ,medium-voltage applications ,multilevel current source inverter ,motor drives ,phase-shifted carrier SPWM ,STATCOM ,electricity forecasting ,CNN-LSTM ,very short-term forecasting (VSTF) ,short-term forecasting (STF) ,medium-term forecasting (MTF) ,long-term forecasting (LTF) ,asynchronous motor ,linear active disturbance rejection control ,error differentiation ,vector control ,renewable energy ,solar power plant ,Data Envelopment Analysis (DEA) ,Fuzzy Analytical Network Process (FANP) ,Fuzzy Theory - Abstract
Summary: Artificial intelligence techniques, such as expert systems, fuzzy logic, and artificial neural network techniques have become efficient tools in modeling and control applications. For example, there are several benefits in optimizing cost-effectiveness, because fuzzy logic is a methodology for the handling of inexact, imprecise, qualitative, fuzzy, and verbal information systematically and rigorously. A neuro-fuzzy controller generates or tunes the rules or membership functions of a fuzzy controller with an artificial neural network approach. There are new instantaneous power theories that may address several challenges in power quality. So, this book presents different applications of artificial intelligence techniques in advanced high-tech electronics, such as applications in power electronics, motor drives, renewable energy systems and smart grids.
8. AI and Financial Markets.
- Author
-
Hamori, Shigeyuki, Takiguchi, Tetsuya, and Hamori, Shigeyuki
- Subjects
Economics, finance, business & management ,algorithmic trading ,Stop Loss ,Turtle ,ATR ,community finances ,fiscal flexibility ,individualized financial arrangements ,sustainable financial services ,price momentum ,hidden markov model ,asset allocation ,blockchain ,BlockCloud ,Artificial Intelligence ,consensus algorithms ,exchange rates ,fundamentals ,prediction ,random forest ,support vector machine ,neural network ,deep reinforcement learning ,financial market simulation ,agent based simulation ,artificial market ,simulation ,CAR regulation ,portfolio ,contract for difference ,CfD ,reinforcement learning ,RL ,neural networks ,long short-term memory ,LSTM ,Q-learning ,deep learning ,uncertainty ,economic policy ,text mining ,topic model ,yield curve ,term structure of interest rates ,machine learning ,autoencoder ,interpretability - Abstract
Summary: Artificial intelligence (AI) is regarded as the science and technology for producing an intelligent machine, particularly, an intelligent computer program. Machine learning is an approach to realizing AI comprising a collection of statistical algorithms, of which deep learning is one such example. Due to the rapid development of computer technology, AI has been actively explored for a variety of academic and practical purposes in the context of financial markets. This book focuses on the broad topic of "AI and Financial Markets", and includes novel research associated with this topic. The book includes contributions on the application of machine learning, agent-based artificial market simulation, and other related skills to the analysis of various aspects of financial markets.
9. The Digital Health in the Pandemic Era.
- Author
-
Giansanti, Daniele and Giansanti, Daniele
- Subjects
Medicine ,Mental health services ,n/a ,digital contact tracing ,IMMUNI app ,COVID-19 ,students ,digital care visit ,online consultation ,medical staff ,healthcare personnel ,user experience ,magnetic resonance imaging (MRI) ,brain tumor ,machine learning ,digital health ,e-health ,pandemic ,physical activity ,performance evaluation ,eHealth ,self-care ,chronic diseases ,mental health ,mindfulness ,mobile health ,social isolation ,mental stress ,feature selection ,artificial intelligence ,human health ,lock down ,normative activation model ,COVID-19 prevention ,prevention intention ,IoT ,obesity ,classification ,regression ,real-time system ,COVID-19 pandemic ,contact tracing ,CNN ,chest X-ray images ,hybrid learning ,computer-aided diagnosis ,remote psychotherapy ,psychotherapy via telephone ,psychotherapy via videoconferencing ,tele-health ,e-mental-health ,psychotherapy ,qualitative psychotherapy research ,mixed-methods psychotherapy research ,exergaming ,breast neoplasms ,physical function ,telehealth ,(d)health literacy ,health literacy ,health intervention ,health strategy ,medical data ,medical imaging ,data classification ,image detection ,YOLOv4 ,logistic regression ,AI ,deep learning ,chatbot ,health ,health domain - Abstract
Summary: Digital health, virtual assistance, and telemedicine are terms often used interchangeably to refer to remote medical assistance, monitoring and care. Several studies and insights have developed these issues, analyzing the advantages and disadvantages and successes and failures and offering reflections on the implications and issues of these technologies in the health domain. The results of these investigations are affecting the redesign of hospital and outpatient management based on digital innovation using eHealth and mHealth. During the COVID-19 pandemic, this approach made it possible to offer assistance and continue care at home, protecting patients, preserving health workers, limiting the spread of the virus, and reducing the need for hospitalization. This reprint contains contributions dealing with the development of DH during the COVID-19 pandemic. The contributions are from various experts in different fields regarding the application of digital health, which, in some cases is also integrated with artificial intelligence, including digital contact tracing, mHealth, virtual reality, mental health, physiology, and rehabilitation.
10. Advances in Public Transport Platform for the Development of Sustainability Cities.
- Author
-
Corchado, Juan M., Larriba-Pey, Josep L., Chamoso, Pablo, De la Prieta, Fernando, and Corchado, Juan M.
- Subjects
Technology: general issues ,History of engineering & technology ,Environmental science, engineering & technology ,optimization models ,timetable ,passenger waiting time ,vehicle occupancy ratio ,intelligent transportation systems ,demand prediction ,taxi recommendation ,vehicle social network ,ride-hailing ,urban rail transit (URT) ,exploratory data analysis (EDA) ,data envelopment analysis (DEA) ,sustainable transport systems ,intelligent transportation systems (ITS) ,big-data applications ,dynamic bus travel time prediction ,wide and deep ,data fusion ,attention ,recurrent neural network ,deep neural networks ,intelligent transportation ,railway ,CPS ,security ,safety ,critical infrastructure ,carsharing ,data analysis ,delays ,demand ,public transit ,taxi ,complex network analysis ,centrality measures ,network robustness ,ridership patterns ,clustering analysis ,passenger flow ,Barcelona underground ,artificial intelligence ,Big Data analytics ,forecasting systems ,recommender system ,Fintech ,passenger traffic ,artificial neural network ,regression analysis ,reputation algorithm ,users' reputation ,transport ,software application ,deep learning ,energy consumption ,sustainable cities ,transfer learning ,wastewater treatment plants ,unmanned aerial vehicles (UAVs) ,multi-objective optimization ,integer programming ,GLPK ,variable neighborhood search ,search and rescue ,learning recommender system ,learning object ,learning videos ,content-based ,collaborative filtering ,users' profiling ,data extraction ,natural language processing ,mapping application ,time series forecasting ,HTM ,regression ,machine intelligence ,cyber-attack detection ,IoT ,trust ,energy trading ,trusted negotiations ,n/a - Abstract
Summary: Modern societies demand high and varied mobility, which in turn requires a complex transport system adapted to social needs that guarantees the movement of people and goods in an economically efficient and safe way, but all are subject to a new environmental rationality and the new logic of the paradigm of sustainability. From this perspective, an efficient and flexible transport system that provides intelligent and sustainable mobility patterns is essential to our economy and our quality of life. The current transport system poses growing and significant challenges for the environment, human health, and sustainability, while current mobility schemes have focused much more on the private vehicle that has conditioned both the lifestyles of citizens and cities, as well as urban and territorial sustainability. Transport has a very considerable weight in the framework of sustainable development due to environmental pressures, associated social and economic effects, and interrelations with other sectors. The continuous growth that this sector has experienced over the last few years and its foreseeable increase, even considering the change in trends due to the current situation of generalized crisis, make the challenge of sustainable transport a strategic priority at local, national, European, and global levels. This Special Issue will pay attention to all those research approaches focused on the relationship between evolution in the area of transport with a high incidence in the environment from the perspective of efficiency.
11. The Artificial Intelligence in Digital Pathology and Digital Radiology: Where Are We?
- Author
-
Giansanti, Daniele and Giansanti, Daniele
- Subjects
Medical equipment & techniques ,n/a ,eHealth ,medical devices ,mHealth ,digital radiology ,picture archive and communication system ,artificial intelligence ,electronic surveys ,chest CT ,chest radiography ,AI ,radiology ,awareness ,radiographers ,radiologists ,e-health ,m-health ,digital-pathology ,cytology ,histology ,diagnostic pathology ,breast cancer ,bibliometric analysis ,healthcare ,medical imaging ,VOSviewer ,digital-radiology ,artificial-intelligence ,acceptance ,consensus ,information technology ,cardiology ,imaging ,cervical cancer screening ,colposcopy ,deep learning ,machine learning ,medical students ,perceptions ,digitization in medicine - Abstract
Summary: This book is a reprint of the Special Issue entitled "The Artificial Intelligence in Digital Pathology and Digital Radiology: Where Are We?". Artificial intelligence is extending into the world of both digital radiology and digital pathology, and involves many scholars in the areas of biomedicine, technology, and bioethics. There is a particular need for scholars to focus on both the innovations in this field and the problems hampering integration into a robust and effective process in stable health care models in the health domain. Many professionals involved in these fields of digital health were encouraged to contribute with their experiences. This book contains contributions from various experts across different fields. Aspects of the integration in the health domain have been faced. Particular space was dedicated to overviewing the challenges, opportunities, and problems in both radiology and pathology. Clinal deepens are available in cardiology, the hystopathology of breast cancer, and colonoscopy. Dedicated studies were based on surveys which investigated students and insiders, opinions, attitudes, and self-perception on the integration of artificial intelligence in this field.
12. The Application of Computer Techniques to ECG Interpretation.
- Author
-
Macfarlane, Peter and Macfarlane, Peter
- Subjects
Medicine ,electrocardiographic imaging (ECGI) ,heart failure (HF) ,cardiac resynchronization therapy (CRT) ,ultrasound ,strain ,speckle tracking echocardiography ,in silico ,electrophysiology ,electrocardiogram ,ECG ,cardiac disease ,arrhythmia ,ischemia ,standardization ,computerized ECG ,personalized medicine ,telemedicine ,digital ECG data interchange protocol ,eHealth ,ECG equipment ,computerized electrocardiograph ,ECG analysis algorithms ,computerized ECG interpretation ,interatrial block ,partial interatrial block ,advanced interatrial block ,atypical patterns ,electrocardiogram (ECG) ,automated ECG analysis ,CSE study ,age ,sex ,race ,historical aspects ,electronic cohort ,mortality ,big data ,telehealth ,alarm fatigue ,annotation of ECG data ,arrhythmia alarms ,intensive care unit ,patient monitoring ,ambulatory ECG ,machine learning ,deep learning ,pattern recognition ,noise reduction ,Holter ECG ,ECG interpretation ,artificial intelligence ,body surface mapping ,electrocardiographic imaging ,image processing ,clinical applications ,n/a - Abstract
Summary: This book presents some of the latest available information on automated ECG analysis written by many of the leading researchers in the field. It contains a historical introduction, an outline of the latest international standards for signal processing and communications and then an exciting variety of studies on electrophysiological modelling, ECG Imaging, artificial intelligence applied to resting and ambulatory ECGs, body surface mapping, big data in ECG based prediction, enhanced reliability of patient monitoring, and atrial abnormalities on the ECG. It provides an extremely valuable contribution to the field.
13. Image and Video Processing and Recognition Based on Artificial Intelligence.
- Author
-
Park, Kang Ryoung, Lee, Sangyoun, Kim, Euntai, and Park, Kang Ryoung
- Subjects
Technology: general issues ,emotion recognition ,brain computer interface ,bag of deep features ,continuous wavelet transform ,face image analysis ,deep learning ,face parsing ,facial attributes classification ,building extraction ,convolutional neural networks ,mask R-CNN ,high-resolution remote sensing image ,autoencoders ,semi-supervised learning ,computer vision ,pathology ,epidermis ,skin ,image processing ,generative models ,generative adversarial net ,depth map ,super-resolution ,guidance ,residual network ,channel interaction ,pose estimation ,body orientation ,multi-person ,multi-task ,surface defect detection ,active learning ,generative adversarial network ,presentation attack detection ,artificial image generation ,presentation attack face images ,ultrasound image ,malignant thyroid nodule ,artificial intelligence ,weighted binary cross-entropy loss ,infrared circumferential scanning system ,target recognition ,deep convolutional neural networks ,data augmentation ,transfer learning ,bounding box regression ,loss function ,medical image fusion ,convolutional neural network ,image pyramid ,multi-scale decomposition ,armature ,surface inspection ,action recognition ,social robotics ,common spatial patterns ,vehicle recognition ,multi resolution network ,optimization ,semantic segmentation ,global context ,local context ,fully convolutional networks ,image-to-image conversion ,image de-raining ,label to photos ,edges to photos ,generative adversarial network (GAN) ,remote sensing ,helicopter footage ,crowd counting ,multitask learning ,normalized cross-correlation ,Marr wavelets ,entropy and response ,graph matching ,RANSAC ,GC-LSTM model ,typhoon ,satellite image ,prediction system ,monocular depth estimation ,feature distillation ,joint attention ,finger-vein recognition ,camera position ,finger position ,lighting ,unobserved database ,heterogeneous database ,domain adaptation ,cycle-consistent adversarial networks ,SDUMLA-HMT-DB ,HKPolyU-DB ,biometrics ,face recognition ,single-sample face recognition ,binarized statistical image features ,K-nearest neighbors ,sparse coding ,fast approximation ,homotopy iterative hard thresholding ,object recognition ,character recognition ,orthogonal polynomials ,orthogonal moments ,Krawtchouk polynomials ,Tchebichef polynomials ,support vector machine - Abstract
Summary: This book includes 23 published papers on Special issues of "Image and Video Processing and Recognition Based on Artificial Intelligence" in the journal Sensors. The purpose of this Special Issue was to invite high-quality and state-of-the-art academic papers on challenging issues in the field of AI-based image and video processing and recognition.
14. Data Analytics and Applications of the Wearable Sensors in Healthcare.
- Author
-
Syed Abdul, Shabbir, Luque, Luis Fernandez, Garcia-Gomez, Juan Miguel, Garcia-Zapirain, Begoña, Hsueh, Pei-Yun, and Syed Abdul, Shabbir
- Subjects
Humanities ,Social interaction ,eHealth ,wearable ,monitoring ,services ,integration ,IoT ,Telemedicine ,wearable sensors ,multivariate analysis ,longitudinal study ,functional decline ,exercise intervention ,accidental falls ,fall detection ,real-world ,signal analysis ,performance measures ,non-wearable sensors ,accelerometers ,cameras ,machine learning ,smart textiles ,healthcare ,talking detection ,activity recognition and monitoring ,patient health and state monitoring ,wearable sensing ,orientation-invariant sensing ,motion sensors ,accelerometer ,gyroscope ,magnetometer ,pattern classification ,artificial intelligence ,supervised machine learning ,predictive analytics ,hemodialysis ,non-contact sensor ,heart rate ,respiration rate ,heart rate variability ,time-domain features ,frequency-domain features ,principal component analysis ,behaviour analysis ,classifier efficiency ,personal risk detection ,one-class classification ,actigraphy ,encoding ,data compression ,denoising ,edge computing ,signal processing ,wearables ,activity monitoring ,citizen science ,cluster analysis ,physical activity ,sedentary behavior ,walking ,energy expenditure ,wearable device ,impedance pneumography ,neural network ,mechanocardiogram (MCG) ,smart clothes ,heart failure (HF) ,left ventricular ejection fraction (LVEF) ,technology acceptance model (TAM) ,physical activity classification ,free-living ,GENEactiv accelerometer ,Gaussian mixture model ,hidden Markov model ,wavelets ,skill assessment ,deep learning ,LSTM ,state space model ,probabilistic inference ,latent features ,human activity recognition ,MIMU ,genetic algorithm ,feature selection ,classifier optimization ,bispectrum ,entropy ,feature extraction ,heat stroke ,filtering algorithm ,physiological parameters ,exercise experiment ,biomedical signal processing ,wearable biomedical sensors ,wireless sensor network ,respiratory monitoring ,optoelectronic plethysmography ,biofeedback ,biomedical technology ,exercise therapy ,orthopedics ,mobile health ,qualitative ,human factors ,inertial measurement unit ,disease prevention ,occupational healthcare ,P-Ergonomics ,precision ergonomics ,musculoskeletal disorders ,wellbeing at work ,electrocardiogram ,conductive gels ,noncontact electrode ,myocardial ischemia ,pacemaker ,ventricular premature contraction ,upper extremity ,motion ,action research arm test ,activities of daily living ,IoT wearable monitor ,health ,posture analysis ,spinal posture ,wearable sensor ,embedded system ,recurrent neural networks ,physical workload ,wearable systems for healthcare ,machine learning for real-time applications ,actigraph ,body worn sensors ,clothing sensors ,cross correlation analysis ,healthcare movement sensing ,wearable devices ,calibration ,inertial measurement units ,human movement ,physical activity type ,real-life ,GPS ,GIS ,n/a - Abstract
Summary: This book provides a collection of comprehensive research articles on data analytics and applications of wearable devices in healthcare. This Special Issue presents 28 research studies from 137 authors representing 37 institutions from 19 countries. To facilitate the understanding of the research articles, we have organized the book to show various aspects covered in this field, such as eHealth, technology-integrated research, prediction models, rehabilitation studies, prototype systems, community health studies, ergonomics design systems, technology acceptance model evaluation studies, telemonitoring systems, warning systems, application of sensors in sports studies, clinical systems, feasibility studies, geographical location based systems, tracking systems, observational studies, risk assessment studies, human activity recognition systems, impact measurement systems, and a systematic review. We would like to take this opportunity to invite high quality research articles for our next Special Issue entitled "Digital Health and Smart Sensors for Better Management of Cancer and Chronic Diseases" as a part of Sensors journal.
15. Clinical Medicine for Healthcare and Sustainability.
- Author
-
Meen, Teen-Hang, Matsumoto, Yusuke, Lee, Kuan-Han, and Meen, Teen-Hang
- Subjects
Medicine ,sarcopenia ,bioimpedance analysis ,computed tomography ,discordance ,effect ,protection ,catheter ,hemodialysis ,meta-analysis ,trial sequential analysis ,Long-term oxygen therapy ,home mechanical ventilation ,patient-reported experience measures ,quality of care ,healthcare ,sustainability ,hepatocellular carcinoma ,health-related quality of life ,minimal clinically important difference ,survival ,serum urate ,menopause ,hypertension ,xanthine dehydrogenase ,cross-sectional cohort study ,diabetic foot ulcer ,peripheral arterial disease ,incidence ,prevalence ,cost ,National Health Insurance Service data ,erythrodermic psoriasis ,secukinumab ,addiction ,smoking ,alcohol ,cannabis ,virtual reality ,musculoskeletal disorders ,randomized controlled tria ,ceftaroline ,ceftriaxone ,community-acquired pneumonia ,safety ,eravacycline ,complicated intra-abdominal infection ,efficacy ,mortality ,laparoscopic ,open surgery ,non-metastatic colorectal cancer ,surgical complication ,oncologic outcome ,single surgeon experience ,doripenem ,acute bacterial infection ,pneumonia ,intra-abdominal infection ,complicated urinary tract infection ,ultrasound-guided injection ,laser assisted ,long-axis injection ,chronic disease ,multimorbidity ,suicidal thoughts ,suicidal plans ,stroke ,post-acute care ,medical referral system ,propensity score matching ,resistance training ,arterial pressure ,disease prevention ,caffeine ,older adults ,frailty ,medication ,primary care ,white matter hyperintensity ,MRI ,healthcare quotient ,chronic ,older adults living in super-aging society ,mild cognitive impairment ,walking speed ,depression ,urinary tract infection ,rapid culture ,antibiotic susceptibility testing (AST), evidence-based prescription ,antibiotics ,antimicrobial resistance (AMR), rapid diagnostics ,prediction ,deep learning ,conventional neural network ,bariatric surgery ,hospital emergency department ,queuing theory ,decision support ,cost optimization ,health behavior ,socioeconomic status ,Korea ,cardiovascular disease ,postprandial ,hypotension ,blood pressure ,elderly ,lung cancer ,physical activity ,season ,preoperative ,wearable ,macrosomia ,large for gestational age ,machine learning ,ensemble methods ,sensitivity ,specificity ,clinical deterioration ,early medical intervention ,electronic health records ,hospital rapid response team ,intensive care units ,medical records system ,computerized ,osteoporosis screening ,artificial intelligence ,convolutional neural networks ,dental panoramic radiographs ,palliative care ,nursing homes ,symptom assessment ,drug therapy ,therapeutics ,longitudinal studies ,occupational medicine ,forensic medicine ,insurance medicine ,psychoactive substances ,clinical ,forensic ,law ,ethics ,uric acid ,risk factor ,epidemiology ,cardiometabolic diseases ,healthcare and sustainability ,therapy of internal medicine diseases - Abstract
Summary: When the domestic government, the private sector, and people in various professional fields talk about long-term care issues, they all focus on creating a warm and home-like care institution. However, we actively emphasize the importance of community-based long-term care. For "aging in place", the development of domestic non-institutional care is still in its infancy, and some long-term care needs must still be met through institutional care, and the facilitation of the extension or outreach of community-based care and respite service platforms for the development of community-based long-term care still rely on institutional care. The history of the development of long-term care in Taiwan is much shorter than that of Japan, Europe, the United States, and Canada. Despite years of hard work and rapid development, the long-term care resources needed to establish a complete system in terms of universalization, fairness, accessibility, and selectivity are not available. In the future, based on the soundness of institutional care, it hoped that outreach will move toward the goals of community care and aging in place. We hope the studies in this Special Issue will help further develop clinical medicine for healthcare and stainability.
16. Artificial Intelligence and Cognitive Computing. Methods, Technologies, Systems, Applications and Policy Making.
- Author
-
Lytras, Miltiadis, Visvizi, Anna, and Lytras, Miltiadis
- Subjects
Information technology industries ,data mining ,decision-making system ,rough set ,mixed integer linear programming ,assembly clearance ,diesel engine quality ,Internet of things ,Wireless nodes ,Hybrid clustering ,Multi-hop routing ,Network lifetime ,Artificial intelligence ,data envelopment analysis ,decision making ,artificial intelligence ,performance ,visual analytics ,system ,air quality ,spatiotemporal ,multivariate ,dimension reduction ,clustering ,regular patterns ,anomalies ,speech recognition ,Long Short Term Memory (LSTM) ,speech output correction ,most-matching ,empirical correlations ,rheological properties ,real-time ,water-based drill-in fluid ,artificial neural network ,elastic parameters ,Poisson's ratio ,sandstone ,self-adaptive differential evolution ,total organic carbon ,barnett shale ,devonian shale ,fishbone multilateral wells ,predictive models ,well productivity ,international research ,knowledge map visualization ,policy documents quantification ,research hotspot ,policy keyword ,minimum miscibility pressure (MMP) ,CO2 flooding ,new models ,face recognition ,security ,spoofing ,histogram of oriented gradients ,smart cities ,deep learning ,LSTM ,neural networks ,location prediction ,trajectories ,smart tourism ,static Young's modulus ,sandstone formations ,machine learning ,n/a - Abstract
Summary: Artificial intelligence (AI) is a subject garnering increasing attention in both academia and the industry today. The understanding is that AI-enhanced methods and techniques create a variety of opportunities related to improving basic and advanced business functions, including production processes, logistics, financial management and others. As this collection demonstrates, AI-enhanced tools and methods tend to offer more precise results in the fields of engineering, financial accounting, tourism, air-pollution management and many more. The objective of this collection is to bring these topics together to offer the reader a useful primer on how AI-enhanced tools and applications can be of use in today's world. In the context of the frequently fearful, skeptical and emotion-laden debates on AI and its value added, this volume promotes a positive perspective on AI and its impact on society. AI is a part of a broader ecosystem of sophisticated tools, techniques and technologies, and therefore, it is not immune to developments in that ecosystem. It is thus imperative that inter- and multidisciplinary research on AI and its ecosystem is encouraged. This collection contributes to that.
17. Intelligent Sensors for Human Motion Analysis.
- Author
-
Krzeszowski, Tomasz, Świtoński, Adam, Kepski, Michal, Calafate, Carlos Tavares, and Krzeszowski, Tomasz
- Subjects
Technology: general issues ,History of engineering & technology ,gait recognition ,biometrics ,regularized discriminant analysis ,particle swarm optimization ,grey wolf optimization ,whale optimization algorithm ,FMCW ,vital sign ,XGBoost ,MFCC ,COVID-19 ,3D human pose estimation ,deep learning ,generalization ,optical sensing principle ,modular sensing unit ,plantar pressure measurement ,gait parameters ,3D human mesh reconstruction ,deep neural network ,motion capture ,neural networks ,reconstruction ,gap filling ,FFNN ,LSTM ,BILSTM ,GRU ,pose estimation ,movement tracking ,computer vision ,artificial intelligence ,markerless motion capture ,assessment ,kinematics ,development ,machine learning ,human action recognition ,features fusion ,features selection ,recognition ,fall risk detection ,balance ,Berg Balance Scale ,human tracking ,elderly ,telemedicine ,diagnosis ,precedence indicator ,knowledge measure ,fuzzy inference ,rule induction ,posture detection ,aggregation function ,markerless ,human motion analysis ,gait analysis ,data augmentation ,skeletal data ,time series classification ,EMG ,pattern recognition ,robot ,cyber-physical systems ,RGB-D sensors ,human motion modelling ,F-Formation ,Kinect v2 ,Azure Kinect ,Zed 2i ,socially occupied space ,facial expression recognition ,facial landmarks ,action units ,convolutional neural networks ,graph convolutional networks ,artifact classification ,artifact detection ,anomaly detection ,3D multi-person pose estimation ,absolute poses ,camera-centric coordinates ,deep-learning ,n/a - Abstract
Summary: The book, "Intelligent Sensors for Human Motion Analysis," contains 17 articles published in the Special Issue of the Sensors journal. These articles deal with many aspects related to the analysis of human movement. New techniques and methods for pose estimation, gait recognition, and fall detection have been proposed and verified. Some of them will trigger further research, and some may become the backbone of commercial systems.
18. Applied Mathematics and Computational Physics.
- Author
-
Wood, Aihua and Wood, Aihua
- Subjects
Research & information: general ,Mathematics & science ,radial basis functions ,finite difference methods ,traveling waves ,non-uniform grids ,chaotic oscillator ,one-step method ,multi-step method ,computer arithmetic ,FPGA ,high strain rate impact ,modeling and simulation ,smoothed particle hydrodynamics ,finite element analysis ,hybrid nanofluid ,heat transfer ,non-isothermal ,shrinking surface ,MHD ,radiation ,multilayer perceptrons ,quaternion neural networks ,metaheuristic optimization ,genetic algorithms ,micropolar fluid ,constricted channel ,MHD pulsatile flow ,strouhal number ,flow pulsation parameter ,multiple integral finite volume method ,finite difference method ,Rosenau-KdV ,conservation ,solvability ,convergence ,transmission electron microscopy (TEM) ,convolutional neural networks (CNN) ,anomaly detection ,principal component analysis (PCA) ,machine learning ,deep learning ,neural networks ,Gallium-Arsenide (GaAs) ,radiation-based flowmeter ,two-phase flow ,feature extraction ,artificial intelligence ,time domain ,Boltzmann equation ,collision integral ,convolutional neural network ,annular regime ,scale layer-independent ,petroleum pipeline ,volume fraction ,dual energy technique ,prescribed heat flux ,similarity solutions ,dual solutions ,stability analysis ,RBF-FD ,node sampling ,lebesgue constant ,complex regions ,finite-difference methods ,data assimilation ,model order reduction ,finite elements analysis ,high dimensional data ,welding - Abstract
Summary: As faster and more efficient numerical algorithms become available, the understanding of the physics and the mathematical foundation behind these new methods will play an increasingly important role. This Special Issue provides a platform for researchers from both academia and industry to present their novel computational methods that have engineering and physics applications.
19. Low Back Pain (LBP)
- Author
-
Denaro, Vincenzo, Iavicoli, Sergio, Russo, Fabrizio, Vadalà, Gianluca, and Denaro, Vincenzo
- Subjects
Technology: general issues ,Environmental science, engineering & technology ,low back pain (LBP) ,standing position ,musculoskeletal pain ,sedentary behaviour ,back pain ,Google Trends ,infodemiology ,seasonality ,Wikipedia ,back problems ,Low Back Pain Scale ,maximum voluntary isometric contraction ,postural stability ,unexpected external postural perturbations ,disability ,insurance ,low back pain ,lumbar decompression ,lumbar fusion ,musculoskeletal disorders ,occupational health ,pain ,return to work ,satisfaction ,manual therapy ,kinesiophobia ,fear of pain ,Australian method ,Neurac ,chronic ,underserved ,African American ,Latino ,older adults ,workload ,wearable assistive device ,occupational back-support exoskeleton ,EMG ,handling task ,lumbalgia ,physical activity ,prevention ,public health ,occupational safety and health ,risk assessment ,occupational disorder ,knowledge ,rehabilitation nurses ,patient care ,unemployment ,gender difference ,population attributable fraction ,cross-sectional studies ,orthopaedics ,artificial intelligence ,computer vision ,digital image processing ,deep learning ,decision support systems ,computer aided diagnosis ,sub-threshold lumbar instability ,non-radiological lumbar instability ,lumbar instability ,radiography ,lumbar translation ,lumbar rotation ,screening tool ,X-ray ,sensitivity ,specificity ,workplace interventions ,workers ,work ability ,systematic review ,meta-analysis ,cognitive behavioral therapy ,mindfulness-based stress reduction ,depression ,fear-avoidance beliefs ,absenteeism ,epidemiology ,workplace ,epidural steroid injections ,lumbosacral radicular pain ,disk herniation ,canal stenosis ,review ,pelvic incidence ,hip-knee line ,anthropometry ,ROC curve ,reliability ,MRI ,CT ,bone metastasis ,bone cancer ,lung cancer ,prostate cancer ,machine learning ,radiomics ,signature ,spinal load ,core stability ,ergonomics ,low-back pain ,lower extremity - Abstract
Summary: Low back pain (LBP) is a major public health problem, being the most commonly reported musculoskeletal disorder (MSD) and the leading cause of compromised quality of life and work absenteeism. Indeed, LBP is the leading worldwide cause of years lost to disability, and its burden is growing alongside the increasing and aging population. The etiology, pathogenesis, and occupational risk factors of LBP are still not fully understood. It is crucial to give a stronger focus to reducing the consequences of LBP, as well as preventing its onset. Primary prevention at the occupational level remains important for highly exposed groups. Therefore, it is essential to identify which treatment options and workplace-based intervention strategies are effective in increasing participation at work and encouraging early return-to-work to reduce the consequences of LBP. The present Special Issue offers a unique opportunity to update many of the recent advances and perspectives of this health problem. A number of topics will be covered in order to attract high-quality research papers, including the following major areas: prevalence and epidemiological data, etiology, prevention, assessment and treatment approaches, and health promotion strategies for LBP. We have received a wide range of submissions, including research on the physical, psychosocial, environmental, and occupational perspectives, also focused on workplace interventions.
Catalog
Discovery Service for Jio Institute Digital Library
For full access to our library's resources, please sign in.