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Keywords: Chicago; State:Illinois; United States; North and Central America; Algorithms; Cyborgs; Emerging Technologies; Health and Medicine; Machine Learning EN Chicago State:Illinois United States North and Central America Algorithms Cyborgs Emerging Technologies Health and Medicine Machine Learning 380 380 1 05/22/23 20230526 NES 230526 2023 MAY 28 (NewsRx) -- By a News Reporter-Staff News Editor at Medical Devices & Surgical Technology Week -- Fresh data on Machine Learning are presented in a new report. Machine learning algorithms may be used to compare the risk of failure of specific patient-procedure combinations in the treatment of cartilage defects of the knee. [Extracted from the article]

Keywords: Acid-Base Imbalance; Algorithms; Computers; Diabetes Complications; Diabetes Mellitus; Diabetic Ketoacidosis; Glucose Metabolism Disorders; Health and Medicine; Hospitals; Nutritional and Metabolic Diseases and Conditions; Peptide Hormones; Peptide Proteins; Proinsulin EN Acid-Base Imbalance Algorithms Computers Diabetes Complications Diabetes Mellitus Diabetic Ketoacidosis Glucose Metabolism Disorders Health and Medicine Hospitals Nutritional and Metabolic Diseases and Conditions Peptide Hormones Peptide Proteins Proinsulin 53 53 1 04/17/23 20230420 NES 230420 2023 APR 17 (NewsRx) -- By a News Reporter-Staff News Editor at Diabetes Week -- New study results on diabetic ketoacidosis have been published. Acid-Base Imbalance, Algorithms, Computers, Diabetes Complications, Diabetes Mellitus, Diabetic Ketoacidosis, Glucose Metabolism Disorders, Health and Medicine, Hospitals, Nutritional and Metabolic Diseases and Conditions, Peptide Hormones, Peptide Proteins, Proinsulin. [Extracted from the article]

A recent report from researchers at Birmingham Women's and Children's NHS Foundation Trust discusses the diagnosis and treatment of progressive familial intrahepatic cholestasis (PFIC), a rare liver disorder that primarily affects children. The researchers aimed to provide recommendations for the management of PFIC in clinical practice. They developed an algorithm for the diagnosis and treatment of children with suspected PFIC, which includes the use of licensed inhibitors of ileal bile acid transporters as the first-line treatment. The authors hope that these recommendations will help standardize the management of PFIC and raise awareness of current developments in the field. [Extracted from the article]

The regulatory uses are real: In 2021, more than 100 drug and biologic applications submitted to the FDA included AI/ML components. Keywords: Algorithms; Artificial Intelligence; Bioengineering; Biologics; Biotechnology; Cybersecurity; Cyborgs; Drug Development; Drug Manufacturing; Drugs and Therapies; Emerging Technologies; FDA; Genetic Engineering; Genetically-Engineered Proteins; Government Agencies Offices and Entities; Health and Medicine; Machine Learning; Office of the FDA Commissioner; Public Health; Technology; U.S. Food and Drug Administration EN Algorithms Artificial Intelligence Bioengineering Biologics Biotechnology Cybersecurity Cyborgs Drug Development Drug Manufacturing Drugs and Therapies Emerging Technologies FDA Genetic Engineering Genetically-Engineered Proteins Government Agencies Offices and Entities Health and Medicine Machine Learning Office of the FDA Commissioner Public Health Technology U.S. Food and Drug Administration 497 497 1 05/22/23 20230523 NES 230523 2023 MAY 22 (NewsRx) -- By a News Reporter-Staff News Editor at Clinical Trials Week -- By: Patrizia Cavazzoni, M.D., Director of the Center for Drug Evaluation and Research Artificial intelligence (AI) and machine learning (ML) are no longer futuristic concepts; they are now part of how we live and work. [Extracted from the article]

A new machine-learning algorithm called xFakeSci has been developed by Ahmed Abdeen Hamed, a visiting research fellow at Binghamton University, to detect fake scientific articles produced by artificial intelligence. The algorithm can detect up to 94% of bogus papers, which is nearly twice as successful as other data-mining techniques. Hamed and collaborator Xindong Wu created 50 fake articles for each of three medical topics and compared them to real articles on the same topics. The algorithm analyzes the number of bigrams and how they are linked to other words and concepts in the text to identify patterns that distinguish fake articles from real ones. Hamed plans to expand the range of topics to further develop the algorithm and raise awareness about the issue of fake research papers. [Extracted from the article]

Algorithms, Diagnostics and Screening, Emerging Technologies, Fibromyalgia, Health and Medicine, Linear Discriminant Analysis, Machine Learning, Muscular Diseases and Conditions, Musculoskeletal Diseases and Conditions, Neuromuscular Diseases and Conditions, Rheumatic Diseases and Conditions Keywords: Algorithms; Diagnostics and Screening; Emerging Technologies; Fibromyalgia; Health and Medicine; Linear Discriminant Analysis; Machine Learning; Muscular Diseases and Conditions; Musculoskeletal Diseases and Conditions; Neuromuscular Diseases and Conditions; Rheumatic Diseases and Conditions EN Algorithms Diagnostics and Screening Emerging Technologies Fibromyalgia Health and Medicine Linear Discriminant Analysis Machine Learning Muscular Diseases and Conditions Musculoskeletal Diseases and Conditions Neuromuscular Diseases and Conditions Rheumatic Diseases and Conditions 158 158 1 04/10/23 20230413 NES 230413 2023 APR 13 (NewsRx) -- By a News Reporter-Staff News Editor at Hematology Week -- Research findings on fibromyalgia are discussed in a new report. [Extracted from the article]

This article discusses the use of clustering models or cluster analyses in mental health research and psychology to explore individual heterogeneity. It highlights the lack of guidance on model choice, analytical framework, and reporting requirements in this field. The paper provides an introduction to major algorithms, such as kernel methods and deep learning, and discusses methods for pre-clustering data processing, clustering evaluation, and validation. The article also presents a rapid review of publications in psychology and psychiatry journals, pointing out issues such as a lack of diversity in algorithm choice and reproducibility. Overall, this comprehensive paper offers researchers advanced tools and guidelines to use clustering methods efficiently, robustly, and transparently in mental health and other health application areas. [Extracted from the article]

A preprint abstract discusses the use of machine learning algorithms and heuristic stopping criteria to improve the efficiency of systematic reviews in education and educational psychology. The study conducted a retrospective screening simulation using 27 systematic reviews and found that active learning algorithms reduced screening workload by an average of 50% and saved an estimated 1.64 days of time. The Random Forests algorithm with Sentence Bidirectional Encoder Representations from Transformers performed the best. Additionally, the study found that heuristic stopping rules could retrieve 95% of relevant abstracts, with the most significant gains achieved by stopping the screening process after classifying 7% of irrelevant papers. The performance of the heuristic stopping criteria depended on the active learning algorithm used, the length, and the proportion of relevant papers in the database. This research provides empirical evidence on the effectiveness of machine learning screening algorithms for abstract screening in systematic reviews in education and educational psychology. [Extracted from the article]

A study conducted by researchers at Sichuan University of Science and Engineering in China explores the design of smart senior care (SSC) product app interfaces for the elderly. The researchers use deep learning (DL) technology to optimize the app interface design, taking into consideration the cognitive characteristics and habits of the elderly. The study finds that the proposed model based on the deep-Q-network (DQN) algorithm significantly improves the user experience and satisfaction of the elderly, enhancing their ability to utilize smart products and improve their quality of life. The research provides valuable insights for further research and practice in related fields. [Extracted from the article]

Researchers from the Beijing Institute of Technology in China have proposed a new method for assessing and diagnosing movement disorders in Parkinson's disease using deep learning algorithms. The method involves using the Kinect algorithm to capture and analyze human skeletal points, and then applying a dynamic time regularization algorithm for movement disorder assessment. The researchers found that their algorithm performed better than existing methods, with an error close to 0.03s when compared to a gold-standard motion capture system. This research provides a valuable and feasible approach for assessing Parkinson's dyskinesia. [Extracted from the article]

A recent study conducted by researchers at Hamad Bin Khalifa University in Doha, Qatar, focuses on the use of machine learning and digital signal processing to improve the analysis of electroencephalogram (EEG) signals for medical diagnosis. EEG is a safe and common test that records electrical signals from the brain and has various applications in diagnosing conditions such as epilepsy, Alzheimer's, brain tumors, sleep disorders, and stroke. The study provides a comprehensive review of recent approaches for EEG preprocessing, feature extraction, and diagnosis of brain disorders, aiming to identify reliable algorithms for improving the accuracy of automatic diagnostic systems. The research concludes that the paper can be a valuable resource for researchers and practitioners in the field, offering insights into recent developments and future research directions. [Extracted from the article]

This article discusses the integration of Artificial Intelligence (AI) and Machine Learning (ML) technologies in cancer research. It highlights how these technologies are transforming the diagnosis, treatment, and prevention of cancer by providing sophisticated analytical capabilities. The paper explores the mathematical foundations and practical implementations of AI and ML techniques in various aspects of cancer research, including detection, diagnosis, prognosis, and personalized treatment strategies. It also reviews influential algorithms such as Support Vector Machines (SVM), Convolutional Neural Networks (CNNs), and clustering techniques, and their roles in improving diagnostic accuracy and treatment efficacy. Please note that this preprint has not been peer-reviewed. [Extracted from the article]

The diagnostic-related genes and diagnostic genes obtained in this paper can be utilized as a reference for clinical sepsis diagnosis. Keywords: Algorithms; Blood Diseases and Conditions; Bloodstream Infection; Cyborgs; Diagnostics and Screening; Emerging Technologies; Genetics; Health and Medicine; Machine Learning; Sepsis; Septicemia EN Algorithms Blood Diseases and Conditions Bloodstream Infection Cyborgs Diagnostics and Screening Emerging Technologies Genetics Health and Medicine Machine Learning Sepsis Septicemia 399 399 1 10/16/23 20231019 NES 231019 2023 OCT 19 (NewsRx) -- By a News Reporter-Staff News Editor at Blood Weekly -- Data detailed on sepsis have been presented. [Extracted from the article]

A report from the University of Oslo discusses the use of machine learning algorithms and heuristic stopping criteria in systematic reviews in education and educational psychology. The study found that using machine learning algorithms for abstract screening reduced the workload of irrelevant records by an average of 58% and saved an estimated 1.66 days of time. The random forests algorithm with sentence bidirectional encoder representations from transformers performed the best. The study also found that heuristic stopping rules could retrieve 95% of relevant abstracts, with the best results achieved by stopping the screening process after classifying 20% of records and consecutively classifying 5% of irrelevant papers. The research provides empirical evidence on the performance of machine learning screening algorithms in this field. [Extracted from the article]

A recent study published in the journal Fuzzy Information and Engineering explores the use of genetic algorithms and fuzzy set theory in epidemic modeling. The research, conducted by the Faculty of Science and Technology at Oxus University in Tashkent, Uzbekistan, emphasizes the need for sophisticated modeling techniques to better understand and predict dynamic scenarios in epidemiology. The study proposes a novel approach that integrates continued fraction theory and a genetic algorithm to fit real-world epidemic data, providing insights crucial for public health planning and control measures. By addressing unexplored facets and bridging gaps in previous research, the study contributes to a more comprehensive understanding of epidemic dynamics and offers a foundation for effective public health strategies in the face of infectious diseases. [Extracted from the article]

A new study conducted by researchers at Tiangong University in Tianjin, China, focuses on the development of a deep learning-based noise reduction method for ambulatory electrocardiogram (ECG) testing. The study aims to improve the clarity of ECG signals obtained during exercise, which are often affected by various noise interferences. The proposed method, which incorporates a multi-kernel convolutional transformer network structure, was found to outperform eight other state-of-the-art methods in terms of noise reduction performance. The researchers believe that this method has the potential to be applied in future noise reduction analysis of clinical dynamic ECG signals. [Extracted from the article]

The article focuses on a review from the University of Applied Sciences and Arts Western Switzerland about machine learning techniques for diagnosing Alzheimer's disease. Topics include the application of machine learning for early diagnosis of Alzheimer's and mild cognitive impairment, the use of magnetic resonance imaging in these techniques, and a comparative analysis of various algorithms' effectiveness in classification performance.

A study conducted at the Hebrew University of Jerusalem explores the role of artificial intelligence (AI) in mental health therapy, specifically focusing on the importance of empathy. The researchers propose a hybrid model where AI supports therapeutic processes without replacing the essential human elements of empathy and emotional engagement. The study emphasizes the nuanced role of empathy in therapy, highlighting that while AI can simulate empathic interactions, it lacks the ability to genuinely connect on an emotional level and care. The research suggests that AI can handle certain tasks in therapy, but human therapists should be involved in situations requiring deep empathy and compassion. [Extracted from the article]

A report from Kerman University of Medical Sciences discusses the use of natural language processing (NLP) to extract cancer concepts from clinical notes automatically. The study systematically reviewed papers that used NLP methods to identify cancer concepts from clinical notes. The researchers found that rule-based algorithms were the most commonly used for concept extraction, and the Systematized Nomenclature of Medicine-Clinical Terms (SNOMED-CT) and Unified Medical Language System (UMLS) were the most commonly used terminologies. The study concluded that the use of NLP for extracting cancer concepts has increased in recent years, and suggested that future studies use rule-based algorithms for extracting concepts of other diseases as well. [Extracted from the article]

Bones of mice with osteoporosis that received the treatment were similar to those of the control group, and the treatment showed no evidence of toxicity. Keywords: Algorithms; American Chemical Society; Antiinfectives; Antimalarial Agents; Antiprotozoal Agents; Asia; Bone Research; Chemistry; China; Drugs and Therapies; Genetics; Health and Medicine; Metabolic Bone Diseases and Conditions; Mosquito-Borne Diseases; Musculoskeletal Diseases and Conditions; Osteoporosis EN Algorithms American Chemical Society Antiinfectives Antimalarial Agents Antiprotozoal Agents Asia Bone Research Chemistry China Drugs and Therapies Genetics Health and Medicine Metabolic Bone Diseases and Conditions Mosquito-Borne Diseases Musculoskeletal Diseases and Conditions Osteoporosis 357 357 1 10/30/23 20231103 NES 231103 2023 NOV 3 (NewsRx) -- By a News Reporter-Staff News Editor at Zika & Mosquito Week -- Correction (): The paper's title has been corrected to "Deep Learning-Predicted Dihydroartemisinin Rescues Osteoporosis by Maintaining Mesenchymal Stem Cell Stemness through Activating Histone 3 Lys 9 Acetylation Artificial intelligence has exploded in popularity and is being harnessed by some scientists to predict which molecules could treat illnesses, or to quickly screen existing medicines for new applications. [Extracted from the article]

To this end, this paper proposes an agent-based algorithm for the protection for user privacy health topics based on identity replacement." Keywords: Zhejiang; People's Republic of China; Asia; Engineering; Algorithms; Cybersecurity; Health and Medicine; Public Health EN Zhejiang People's Republic of China Asia Engineering Algorithms Cybersecurity Health and Medicine Public Health 8478 8478 1 10/30/23 20231103 NES 231103 2023 NOV 3 (NewsRx) -- By a News Reporter-Staff News Editor at Health & Medicine Week -- New research on Engineering is the subject of a report. [Extracted from the article]

Jammu Kashmir, India, Asia, Algorithms, Cancer, Cervical Cancer, Diagnostics and Screening, Health and Medicine, Oncology, Women's Health Keywords: Jammu Kashmir; India; Asia; Algorithms; Cancer; Cervical Cancer; Diagnostics and Screening; Health and Medicine; Oncology; Women's Health EN Jammu Kashmir India Asia Algorithms Cancer Cervical Cancer Diagnostics and Screening Health and Medicine Oncology Women's Health 1014 1014 1 10/03/23 20231006 NES 231006 2023 OCT 3 (NewsRx) -- By a News Reporter-Staff News Editor at Women's Health Weekly -- A new study on Oncology - Cervical Cancer is now available. [Extracted from the article]

This paper compares AI (artificial intelligence) algorithms in diagnosing and predicting gastric cancer based on types of AI algorithms, sample size, accuracy, sensitivity, and specificity. Keywords: Algorithms; Artificial Intelligence; Cancer; Emerging Technologies; Gastric Cancer; Gastroenterology; Health and Medicine; Machine Learning; Oncology EN Algorithms Artificial Intelligence Cancer Emerging Technologies Gastric Cancer Gastroenterology Health and Medicine Machine Learning Oncology 427 427 1 03/23/23 20230321 NES 230321 2023 MAR 21 (NewsRx) -- By a News Reporter-Staff News Editor at Cancer Weekly -- A new study on artificial intelligence is now available. [Extracted from the article]

Keywords: Algorithms; Cancer; DNA Damage; DNA Research; Deoxyribonucleic Acid; Esophageal Cancer; Gastroenterology; Genetics; Health and Medicine; Oncology; Proteomics; Rehabilitation; Technology; Therapy EN Algorithms Cancer DNA Damage DNA Research Deoxyribonucleic Acid Esophageal Cancer Gastroenterology Genetics Health and Medicine Oncology Proteomics Rehabilitation Technology Therapy 603 603 1 03/23/23 20230314 NES 230314 2023 MAR 14 (NewsRx) -- By a News Reporter-Staff News Editor at Immunotherapy Weekly -- Data detailed on esophageal cancer have been presented. This paper proposed a study on DNA damage repair of cancer cells based on goal directed fluid therapy combined with rehabilitation therapy, aiming to optimize the traditional treatment of esophageal cancer by using goal directed fluid therapy technology. [Extracted from the article]

Researchers at NYU Tandon School of Engineering have developed a new technology that could allow stroke patients to undergo rehabilitation exercises at home. The technology involves using a smartphone strapped to the forearm and a low-cost gaming controller called the Novint Falcon to track wrist movements. By combining data from the smartphone's motion sensors with the controller's measurements through machine learning, the researchers were able to predict wrist angles with over 90% accuracy. This technology has the potential to increase access to post-stroke care and improve the quality of life for stroke patients. [Extracted from the article]

A recent study from Tianjin University in China discusses the progress made in developing methods for predicting epileptic seizures based on EEG data. The researchers highlight the importance of early prediction and intervention in improving the quality of life for epilepsy patients. The study reviews commonly used databases, methods for pre-processing and analyzing EEG data, and limitations of current algorithms. The researchers also compare deep learning algorithms with traditional machine learning methods and suggest that these new technologies may lead to significant breakthroughs in seizure prediction. This research has been peer-reviewed and provides valuable insights for further study in this field. [Extracted from the article]

Researchers from Monash University Malaysia have proposed a new model called the rectified complex spherical fuzzy set (rCTSFS) for the detection of diabetic retinopathy. The model utilizes rectified complex t-spherical fuzzy Dombi-Choquet integral operators and a multi-criteria decision-making algorithm. The researchers found that their proposed algorithm was the only one that produced correct diagnostic results, outperforming 50 other algorithms tested. This research provides a potential advancement in the detection of diabetic retinopathy through the analysis of fundus images. [Extracted from the article]

A research paper from the Dr. Sivanthi Aditanar College of Engineering in Tiruchendur, India, explores the analysis of Bipolar Disorder (BD) using structural magnetic resonance imaging (MRI) and a supervised learning framework. The study aims to identify specific abnormalities in brain cells that indicate BD. The researchers employed a 3D texture analysis approach, extracting texture features from the MRI data and using a supervised learning algorithm called Support Vector Machine (SVM) to classify samples as healthy or abnormal. The results showed promising outcomes, with the SVM model achieving an accuracy of 90.42%. This research provides valuable insights into the application of supervised learning and MRI data analysis for understanding BD. [Extracted from the article]

A study conducted by researchers at Henan Normal University in China has proposed a new method for monitoring the training load of athletes using sensor technology and motion image analysis. The researchers combined the advantages of vision-based motion monitoring and wearable sensor-based motion monitoring to create a method that can be used for motion monitoring anytime and anywhere. They also developed a two-stage neural network motion monitoring algorithm to identify different types of motions separately, which improves the accuracy of recognition. Additionally, the study introduced a data enhancement algorithm based on acceleration data to increase the number of samples without the need for re-collecting data. The results of simulation experiments showed that this method can be applied to real-life situations. [Extracted from the article]

The three stages of the QIP algorithm include: (1) detection of line segments, (2) unraveling of the interlocking pentagons, and (3) quantification of areas. "In this paper, we present a novel three-stage algorithm, called Quantification of Interlocking Pentagons (QIP), which quantifies PCT performance by computing the areas of individual pentagons and their intersection areas, and a balance ratio between the areas of the two individual pentagons. [Extracted from the article]

To address this challenge, the paper introduces an accurate binary prostate cancer classification algorithm that integrates linear support vector machines (SVM) and ridge regression-based four-feature selection algorithms. Keywords: Algorithms; Cancer; Diagnostics and Screening; Health and Medicine; Machine Learning; Oncology; Prostate Cancer; Prostatic Neoplasms; Support Vector Machines EN Algorithms Cancer Diagnostics and Screening Health and Medicine Machine Learning Oncology Prostate Cancer Prostatic Neoplasms Support Vector Machines 1492 1492 1 09/11/23 20230912 NES 230912 2023 SEP 12 (NewsRx) -- By a News Reporter-Staff News Editor at Cancer Weekly -- Investigators publish new report on prostate cancer. [Extracted from the article]

Keywords: Algorithms; Computers; Endoscopy; Health and Medicine; Minimally Invasive Surgical Procedures; Surgery EN Algorithms Computers Endoscopy Health and Medicine Minimally Invasive Surgical Procedures Surgery 686 686 1 08/28/23 20230903 NES 230903 2023 SEP 3 (NewsRx) -- By a News Reporter-Staff News Editor at Medical Devices & Surgical Technology Week -- Research findings on endoscopy are discussed in a new report. Algorithms, Computers, Endoscopy, Health and Medicine, Minimally Invasive Surgical Procedures, Surgery. [Extracted from the article]

A recent study conducted by researchers at the ECE Department in Vijayawada, India, examined the effectiveness of machine learning techniques for the early detection of type 2 diabetes. The researchers analyzed various papers and methodologies, assessing the accuracy of these methods. They proposed a comprehensive framework that utilizes current machine learning algorithms and incorporates novel technologies to enhance the accuracy and reliability of diabetes prediction. The study emphasizes the socio-economic impact of early diabetes detection and highlights the importance of timely interventions in reducing healthcare expenses and improving patient outcomes. The research contributes to global efforts to combat diabetes and improve public health. [Extracted from the article]

A study conducted by researchers at the University of Salerno in Italy has developed a user-friendly algorithm to assist surgeons in pedicle arthrodesis operations for spine surgery. The algorithm uses 3D scans of a patient's vertebra to identify the optimal direction for screw insertion and select the best screws to maximize bone occupation without intersecting each other or going through the walls of the pedicle and vertebral body. The algorithm has been tested on six vertebrae and allows surgeons to freely choose the entry point for the screw. This research represents a novel approach in the field and provides surgeons with a tool for planning their surgeries and creating customized surgical templates. [Extracted from the article]

A research paper from the Kalasalingam Academy of Research and Education in Tamil Nadu, India, introduces a model called Taylor-Tunicate Swarm Algorithm-based Generative Adversarial Networks (Taylor-TSA-based GANs) for cancer prediction. The model incorporates the Taylor series with the Tunicate Swarm Algorithm and uses the Yeo-Johnson transformation for data transformation. The feature fusion is evaluated by Deep Stacked Autoencoder, and the fused feature is given as input to the cancer prediction done by GAN trained by Taylor-TSA. The research concludes that the developed model is effective and efficient, with high accuracy, a low false positive rate, and a high true positive rate. [Extracted from the article]

Keywords: Chennai; India; Asia; Algorithms; Breast Cancer; Breast Cancer Screening; Cancer; Diagnostics and Screening; Health and Medicine; Mammogram; Mammography; Oncology; Risk and Prevention; Women's Health EN Chennai India Asia Algorithms Breast Cancer Breast Cancer Screening Cancer Diagnostics and Screening Health and Medicine Mammogram Mammography Oncology Risk and Prevention Women's Health 234 234 1 06/26/23 20230627 NES 230627 2023 JUN 27 (NewsRx) -- By a News Reporter-Staff News Editor at Women's Health Weekly -- Investigators discuss new findings in Oncology - Breast Cancer. For more information on this research see: Cancer Regions In Mammogram Images Using Anfis Classifier Based Probability Histogram Segmentation Algorithm. [Extracted from the article]

According to the news editors, the research concluded: "This is the first work that utilizes an optimal feature selection model using QICO and QICO-RNN for effective classification of cancer data using gene expression data." Originality/value This paper introduces a new optimal feature selection model using QICO and QICO-based RNN for effective classification of cancer data using gene expression data." For more information on this research see: Cancer Data Classification By Quantum-inspired Immune Clone Optimization-based Optimal Feature Selection Using Gene Expression Data: Deep Learning Approach. [Extracted from the article]

Most of the existing studies around breast cancer classification adopt a single algorithm to fit breast cancer data but ignore the applicability of different breast cancer data features to the model. Keywords: Algorithms; Breast Cancer; Cancer; Cyborgs; Diagnostics and Screening; Emerging Technologies; Health and Medicine; Machine Learning; Oncology; Women's Health EN Algorithms Breast Cancer Cancer Cyborgs Diagnostics and Screening Emerging Technologies Health and Medicine Machine Learning Oncology Women's Health 471 471 1 03/23/23 20230324 NES 230324 2023 MAR 21 (NewsRx) -- By a News Reporter-Staff News Editor at Women's Health Weekly -- Current study results on breast cancer have been published. [Extracted from the article]

The news reporters obtained a quote from the research from the School of Engineering and Design, "This paper reviews noise reduction algorithms in cochlear implants. Keywords: Sligo; Ireland; Europe; Algorithms; Cochlear Implants; Electronics; Health and Medicine; Implant Technology; Medical Devices; Signal Processing; Surgery; Surgical Technology EN Sligo Ireland Europe Algorithms Cochlear Implants Electronics Health and Medicine Implant Technology Medical Devices Signal Processing Surgery Surgical Technology 511 511 1 03/23/23 20230310 NES 230310 2023 MAR 12 (NewsRx) -- By a News Reporter-Staff News Editor at Medical Devices & Surgical Technology Week -- Investigators discuss new findings in Implant Technology - Cochlear Implants. [Extracted from the article]

Nutritional and Metabolic Diseases and Conditions - Type 2 Diabetes Investigators publish new report on type 2 diabetes. In this paper,gradient boosting classifier, AdaBoost classifier, decision treeclassifier, and extra trees classifier machine learning models have beenutilized for identifying chronic diabetes disease. [Extracted from the article]

A recent study conducted at the Central University of Haryana in India has proposed a privacy-preserving collaborative model for the classification of brain tumors using magnetic resonance imaging (MRI) images. The study utilized deep learning and transfer learning algorithms to analyze an open-source dataset of MRI images, which included four types of tumors and no tumor. The researchers found that federated deep learning models, involving multiple clients, outperformed conventional pretrained models in terms of accuracy. The proposed framework offers a solution for early diagnosis of brain tumors while ensuring data privacy for edge devices with limited resources. [Extracted from the article]

A recent study conducted by researchers at the First Affiliated Hospital of Wenzhou Medical University in China explores the use of deep learning algorithms in medical image analysis. The study highlights the importance of employing advanced deep learning techniques in this field, as they have shown impressive results in various areas of healthcare. The researchers categorized and assessed different deep learning techniques, such as Convolutional Neural Networks (CNNs) and Recurrent Neural Networks (RNNs), based on their principles, advantages, limitations, methodologies, and datasets. The study also addresses the challenges that hinder the widespread implementation of deep learning in medical image analysis. The findings of this research provide valuable insights for future studies and advancements in image analysis in medical healthcare research. [Extracted from the article]

Keywords: Algorithms; Cyborgs; Emerging Technologies; Epidemiology; Health and Medicine; Hemic and Immune Systems; Immunology; Lymph Nodes; Lymphoid Tissue; Machine Learning; Neoplasms; Risk and Prevention EN Algorithms Cyborgs Emerging Technologies Epidemiology Health and Medicine Hemic and Immune Systems Immunology Lymph Nodes Lymphoid Tissue Machine Learning Neoplasms Risk and Prevention 4761 4761 1 11/06/23 20231110 NES 231110 2023 NOV 10 (NewsRx) -- By a News Reporter-Staff News Editor at Health & Medicine Week -- A new study on neoplasms is now available. This paper describes the development and validation of a predictive model of the risk of lymph node metastasis among gastric NEN patients based on machine learning platform.". [Extracted from the article]

According to the news editors, the research concluded: "The results show that the proposed framework has superior performance compared to several existing glioma image enhancement methods. image." To enrich the field of glioma image enhancement, this paper proposed a glioma image enhancement framework based on histogram modification and total variational using stochastic parallel gradient descent (SPGD) algorithm.". [Extracted from the article]

Keywords: Guimaraes; Portugal; Europe; Algorithms; Basal Ganglia Diseases and Conditions; Brain Diseases and Conditions; Central Nervous System Diseases and Conditions; Diagnostics and Screening; Health and Medicine; Movement Disorders; Nervous System Diseases and Conditions; Neurodegenerative Diseases and Conditions; Parkinson's Disease; Parkinsonian Disorders; Technology EN Guimaraes Portugal Europe Algorithms Basal Ganglia Diseases and Conditions Brain Diseases and Conditions Central Nervous System Diseases and Conditions Diagnostics and Screening Health and Medicine Movement Disorders Nervous System Diseases and Conditions Neurodegenerative Diseases and Conditions Parkinson's Disease Parkinsonian Disorders Technology 1245 1245 1 11/06/23 20231106 NES 231106 2023 NOV 6 (NewsRx) -- By a News Reporter-Staff News Editor at Pain & Central Nervous System Week -- A new study on Neurodegenerative Diseases and Conditions - Parkinson's Disease is now available. Keywords for this news article include: Guimaraes, Portugal, Europe, Algorithms, Basal Ganglia Diseases and Conditions, Brain Diseases and Conditions, Central Nervous System Diseases and Conditions, Diagnostics and Screening, Health and Medicine, Movement Disorders, Nervous System Diseases and Conditions, Neurodegenerative Diseases and Conditions, Parkinson's Disease, Parkinsonian Disorders, Technology, University of Minho. Guimaraes, Portugal, Europe, Algorithms, Basal Ganglia Diseases and Conditions, Brain Diseases and Conditions, Central Nervous System Diseases and Conditions, Diagnostics and Screening, Health and Medicine, Movement Disorders, Nervous System Diseases and Conditions, Neurodegenerative Diseases and Conditions, Parkinson's Disease, Parkinsonian Disorders, Technology. [Extracted from the article]

Keywords: Msila; Algeria; Algorithms; Cancer; Genetics; Health and Medicine; Oncology EN Msila Algeria Algorithms Cancer Genetics Health and Medicine Oncology 684 684 1 10/30/23 20231031 NES 231031 2023 OCT 31 (NewsRx) -- By a News Reporter-Staff News Editor at Cancer Weekly -- Current study results on Cancer have been published. This paper proposes a new bio-inspired algorithm for cancer classification in gene selection called Binary Grey Wolf Optimization Algorithm (BGWOA), which is based on hybridization between Minimum Redundancy-Maximum Relevance (MRMR) and a novel Binary Grey Wolf algorithm. [Extracted from the article]

This paper presents a comprehensive comparative analysis of six Convolutional Neural Networks and Deep Neural Networks based machine learning models, including simple CNN, VGG16, DenseNet121, ResNet50, InceptionV3, and EfficientNetB3, for the recognition of diabetic retinopathy using fundus photographs. Keywords: Algorithms; Cyborgs; Diabetic Angiopathies; Diabetic Retinopathy; Emerging Technologies; Eye Diseases and Conditions; Health and Medicine; Machine Learning; Networks; Neural Networks; Nutritional and Metabolic Diseases and Conditions; Ophthalmology; Retinal Diseases and Conditions; Retinopathy; Vascular Diseases and Conditions EN Algorithms Cyborgs Diabetic Angiopathies Diabetic Retinopathy Emerging Technologies Eye Diseases and Conditions Health and Medicine Machine Learning Networks Neural Networks Nutritional and Metabolic Diseases and Conditions Ophthalmology Retinal Diseases and Conditions Retinopathy Vascular Diseases and Conditions 107 107 1 10/30/23 20231030 NES 231030 2023 OCT 30 (NewsRx) -- By a News Reporter-Staff News Editor at Diabetes Week -- New study results on diabetic retinopathy have been published. [Extracted from the article]