A University of Idaho lab received $1.3 million from the Department of Defense to study early detection methods for ...

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 ...

The XGBoost model predicts hyperglycemia risk in psoriasis patients with high accuracy, achieving an AUC of 0.821 in the training set. A web-based calculator was developed to facilitate personalized ...

For the first time, researchers have used machine learning – a type of artificial intelligence (AI) – to identify the most important drivers of cancer survival in nearly all the countries in the world ...

This study presents a transfer learning–based method for predicting train-induced environmental vibration. The method applies data fusion to combine physics-based numerical simulations and limited ...

Gas sensing material screening faces challenges due to costly trial-and-error methods and the complexity of multi-parameter ...

Background Annually, 4% of the global population undergoes non-cardiac surgery, with 30% of those patients having at least ...

insights from industryJohanna Uhari-Väänänen & Timo BraggeGroup Leader (Neuropharmacology) - Senior Data ScientistCharles River Laboratories In this interview, industry experts Johanna Uhari-Väänänen ...

Startup SpotitEarly is pioneering an innovative early cancer screening test based on breath samples and powered by artificial intelligence and the strong scent detection of trained dogs. SpotitEarly ...