Background There is a lack of atrial fibrillation (AF) prediction models tailored for individuals without prior ...

New York City-based Icahn School of Medicine at Mount Sinai has developed a machine learning model to estimate disease risk from rare genetic variants using routine clinical data. The model was ...

A machine learning model bests traditional methods for predicting cirrhosis mortality among hospitalized patients.

Stanford University researchers developed a machine learning-based method capable of diagnosing multiple diseases using B cell and T cell receptor sequences. The model, called Machine learning for ...

When genetic testing reveals a rare DNA mutation, doctors and patients are frequently left in the dark about what it actually means.

Researchers say they've trained artificial intelligence models to assess genetic risks for 10 inherited diseases on a spectrum rather than simply "yes/no." ...

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 ...