Sticking to an exercise routine is a challenge many people face. But a research team is using machine learning to uncover what keeps individuals committed to their workouts. Sticking to an exercise ...

Please provide your email address to receive an email when new articles are posted on . Machine learning models may accurately predict outcome measures for patients undergoing MPFL reconstruction.

A team of researchers has successfully predicted abnormal grain growth in simulated polycrystalline materials for the first time -- a development that could lead to the creation of stronger, more ...

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 ...

Performance of Two-Phase Designs for the Time-to-Event Outcome and a Case Study Assessing the Relapse Risk Associated With B-ALL Subtypes Using a real-world, nationwide electronic health ...

A University of Alberta research team has successfully used machine learning as a tool for earlier detection of attention deficit hyperactivity disorder (ADHD) in kindergarten students. In a recent ...

Please provide your email address to receive an email when new articles are posted on . The best model for predicting schizophrenia performed substantially better than the best bipolar ...

Microbial communities are constantly exposed to the invasion of exogenous species, which can significantly alter their composition and function. The capacity of a microbial community to resist ...

Machine learning algorithms utilizing electronic health records can effectively predict two-year dementia risk among American Indian/Alaska Native adults aged 65 years and older, according to a ...

New perk: Easily find new routes and hidden gems, upcoming running events, and more near you. Your weekly Local Running Newsletter has everything you need to lace up! Subscribe today. One of the deep ...