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Development of an Artificial Intelligence-Enabled Electrocardiography to Detect 23 Cardiac Arrhythmias and Predict Cardiovascular Outcomes.

Journal of medical systems
Arrhythmias are common and can affect individuals with or without structural heart disease. Deep learning models (DLMs) have shown the ability to recognize arrhythmias using 12-lead electrocardiograms (ECGs). However, the limited types of arrhythmias...

A machine learning toolkit assisted approach for IMRT fluence map optimization: feasibility and advantages.

Biomedical physics & engineering express
. Traditional machine learning (ML) and deep learning (DL) applications in treatment planning rely on complex model architectures and large, high-quality training datasets. However, they cannot fully replace the conventional optimization process. Thi...

A semi-supervised prototypical network for prostate lesion segmentation from multimodality MRI.

Physics in medicine and biology
Prostate lesion segmentation from multiparametric magnetic resonance images is particularly challenging due to the limited availability of labeled data. This scarcity of annotated images makes it difficult for supervised models to learn the complex f...

Comparison of artificial intelligence-generated and physician-generated patient education materials on early diabetic kidney disease.

Frontiers in endocrinology
BACKGROUND: Diabetic kidney disease (DKD) is a common and serious complication of diabetes mellitus and has become the most important cause of end-stage renal disease (ESRD). In light of the rising prevalence of diabetes, there is a growing imperativ...

A deep learning-based ensemble for autism spectrum disorder diagnosis using facial images.

PloS one
Autism Spectrum Disorder (ASD) is a neurodevelopmental disorder leading to an inability to socially communicate and in extreme cases individuals are completely dependent on caregivers. ASD detection at early ages is crucial as early detection can red...

Social robot PIO intervention for improving cognitive function and depression in older adults with mild to moderate dementia in day care centers: A randomized controlled trial.

PloS one
The increases in the older population, the prevalence of dementia, and the resulting social costs are burdensome to individuals, families, and the nation. This study examines whether the social robot PIO program intervention is effective for cognitiv...

A Multimodal Approach for Early Identification of Mild Cognitive Impairment and Alzheimer's Disease With Fusion Network Using Eye Movements and Speech.

IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society
Detecting Alzheimer's disease (AD) in its earliest stages, particularly during an onset of Mild Cognitive Impairment (MCI), remains challenging due to the overlap of initial symptoms with normal aging processes. Given that no cure exists and current ...

Predictors of Sleep Latency From the Multiple Sleep Latency Test: A Random Forest Investigation in a Community Sample.

Journal of sleep research
This study aimed to advance the understanding of factors that predict mean sleep latency (MSL) on the multiple sleep latency test (MSLT) by applying machine learning methodology on a high-dimensional dataset from a large community sample. A cross-sec...

Transcriptomic Biomarkers in Blood Indicative of the Administration of Recombinant Human Erythropoietin to Thoroughbred Horses.

Drug testing and analysis
Erythropoiesis-stimulating agents (ESAs) continue to be a significant threat to the integrity of human and equine sports. Besides conventional direct testing, monitoring the biomarkers associated with the effects of ESAs may provide a complementary a...