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Evaluation of Hand Action Classification Performance Using Machine Learning Based on Signals from Two sEMG Electrodes.
Sensors (Basel, Switzerland)
Apr 9, 2024
Classification-based myoelectric control has attracted significant interest in recent years, leading to prosthetic hands with advanced functionality, such as multi-grip hands. Thus far, high classification accuracies have been achieved by increasing ...
Validation of Machine Learning-Based Assessment of Major Depressive Disorder from Paralinguistic Speech Characteristics in Routine Care.
Depression and anxiety
Apr 9, 2024
New developments in machine learning-based analysis of speech can be hypothesized to facilitate the long-term monitoring of major depressive disorder (MDD) during and after treatment. To test this hypothesis, we collected 550 speech samples from tele...
Development of a deep-learning algorithm for age estimation on CT images of the vertebral column.
Legal medicine (Tokyo, Japan)
Apr 7, 2024
PURPOSE: The accurate age estimation of cadavers is essential for their identification. However, conventional methods fail to yield adequate age estimation especially in elderly cadavers. We developed a deep learning algorithm for age estimation on C...
Assessing the Influence of B-US, CDFI, SE, and Patient Age on Predicting Molecular Subtypes in Breast Lesions Using Deep Learning Algorithms.
Journal of ultrasound in medicine : official journal of the American Institute of Ultrasound in Medicine
Apr 6, 2024
OBJECTIVES: Our study aims to investigate the impact of B-mode ultrasound (B-US) imaging, color Doppler flow imaging (CDFI), strain elastography (SE), and patient age on the prediction of molecular subtypes in breast lesions.
Development and validation of machine learning models to predict postoperative infarction in moyamoya disease.
Journal of neurosurgery
Apr 5, 2024
OBJECTIVE: Cerebral infarction is a common complication in patients undergoing revascularization surgery for moyamoya disease (MMD). Although previous statistical evaluations have identified several risk factors for postoperative brain ischemia, the ...
Deep learning denoising reconstruction enables faster T2-weighted FLAIR sequence acquisition with satisfactory image quality.
Journal of medical imaging and radiation oncology
Apr 5, 2024
INTRODUCTION: Deep learning reconstruction (DLR) technologies are the latest methods attempting to solve the enduring problem of reducing MRI acquisition times without compromising image quality. The clinical utility of this reconstruction technique ...
Vaginal microbiota molecular profiling and diagnostic performance of artificial intelligence-assisted multiplex PCR testing in women with bacterial vaginosis: a single-center experience.
Frontiers in cellular and infection microbiology
Apr 5, 2024
BACKGROUND: Bacterial vaginosis (BV) is a most common microbiological syndrome. The use of molecular methods, such as multiplex real-time PCR (mPCR) and next-generation sequencing, has revolutionized our understanding of microbial communities. Here, ...
Identification of the best machine learning model for the prediction of driver injury severity.
International journal of injury control and safety promotion
Apr 4, 2024
Predicting the injury severities sustained by drivers engaged in road traffic accidents is a key topic of research in road traffic safety. The current study analyzed the driver injury severity (DIS) using twelve machine learning (ML) algorithms. Thes...
Association between match-related physical activity profiles and playing positions in different tasks: A data driven approach.
Journal of sports sciences
Apr 4, 2024
Assessing the intensity characteristics of specific soccer drills (matches, small-side game, and match-based exercises) could help practitioners to plan training sessions by providing the optimal stimulus for every player. In this paper, we propose a...
Deep Learning for Automated Measurement of Total Cardiac Volume for Heart Transplantation Size Matching.
Pediatric cardiology
Apr 3, 2024
Total Cardiac Volume (TCV)-based size matching using Computed Tomography (CT) is a novel technique to compare donor and recipient heart size in pediatric heart transplant that may increase overall utilization of available grafts. TCV requires manual ...
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