At HRS 2026, Dr. Song Zuo presented evidence that AI can detect atrial fibrillation with over 90% sensitivity, ...

Machine learning models may help identify risk for asthma among children with atopic dermatitis in early life.

Objective This study reviewed the current state of machine learning (ML) research for the prediction of sports-related injuries. It aimed to chart the various approaches used and assess their efficacy ...

Sensor data from wearable devices analyzed over five years reveals walking and posture differences that predict fall risk in Parkinson’s patients. Study: Predicting future fallers in Parkinson’s ...

Developing a Metabolic-Associated Prognostic Index for Risk Stratification and Therapeutic Guidance in Stage I Lung Adenocarcinoma via Multiomics Analysis Using the National Cancer Database, we ...

Innovative machine learning models using routine clinical data offer superior stroke risk prediction in atrial fibrillation, ...

A new study using US health survey data has developed a machine learning model that predicts osteoarthritis risk from exposure to volatile organic compounds (VOCs). The Linear Discriminant Analysis ...

Scientists at the Baylor College of Medicine and collaborating institutions used complementary approaches that integrate exome sequencing and evolutionary action machine learning to identify protein ...

Please provide your email address to receive an email when new articles are posted on . Researchers are using machine learning to identify data-driven PCOS subtypes. Findings may lead to more precise ...

SardineAI Corp announces the release of a fraud risk operations guide focused on the distinction between machine learning vs generative AI as an operational consideration within financial crime ...