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 ...

In an interview with Technology Networks, Dr. Daniel Reker discusses how machine learning is improving data-scarce areas of drug discovery.

DataZapp brings AI and machine learning to deliver affordable, predictive demand generation and marketing data for home ...

Dr. Michael Spaeder of the University of Virginia previews his upcoming HIMSS26 talk on using AI and machine learning to detect potentially catastrophic health events.

A machine learning model incorporating functional assessments predicts one-year mortality in older patients with HF and improves risk stratification beyond established scores. Functional status at ...

As businesses increasingly explore AI solutions, one of the key questions is: Which type of AI delivers more value, generative or predictive? Both bring unique strengths, and choosing (or combining) ...

Researchers sought to determine an effective approach to predict postembolization fever in patients undergoing TACE.

QA teams now use machine learning to analyze past test data and code changes to predict which tests will fail before they run. The technology examines patterns from previous test runs, code commits, ...