Medscape

Advanced Machine Learning Model Predicts Onset of Epilepsy and Depression

A large study applies advanced machine learning to identify shared risk factors and predictors of disease onset in patients with epilepsy and depression.
Healio

Electronic health record-based machine learning models improve OSA prediction

Machine learning models that use electronic health record data to predict obstructive sleep apnea had greater performance than two screening questionnaires, according to a poster presented at SLEEP ...
IEEE

Siamese Convolutional Neural Network for Heartbeat Classification Using Limited 12-Lead ECG Datasets

Abstract: The Electrocardiogram (ECG) is a low-cost exam commonly used to diagnose abnormalities in the cardiac cycle. Over the years, the scientific community has investigated the automatic ...

AI/ML Innovations Inc. Announces Grant of U.S. Patent Expanding Protection for AI-Driven ECG Analysis

Patent covers machine learning techniques for ECG denoising, rhythm classification, sample-level labelling, wearable cardiac ...
AHA/ASA Journals

Contrastive Machine Learning to Quantify Hypertensive Multiorgan Damage and Identify New Disease Phenotypes: A Multinational Multimodal Study

BACKGROUND: Hypertension induces structural and functional damage in multiple organs. Evidence of subclinical damage ...
IEEE

ECG Heartbeat Classification Using Multimodal Fusion

Abstract: Electrocardiogram (ECG) is an authoritative source to diagnose and counter critical cardiovascular syndromes such as arrhythmia and myocardial infarction (MI). Current machine learning ...
Frontiers

Advancements in Smart Diagnostics for Understanding Neurological Behaviors and Biosensing Applications

The intersection of machine learning, biosensing technologies, and neurological behavior analysis presents fertile ground for groundbreaking research and innovation. This research topic aims to bridge ...