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 ...

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 ...

A total of 590 patients were identified, 432 in the development set and 158 in the validation set. The median age was 51 years, and 55.8% (329 of 590) experienced grade 3 or 4 toxicity. The ...

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 ...

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 ...

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 ...

A recent study by Yale researchers demonstrated the potential of a machine learning approach to predict symptoms of post-traumatic stress disorder, or PTSD, for recent trauma survivors. Researchers ...

A team of Lehigh University researchers has successfully predicted abnormal grain growth in simulated polycrystalline materials for the first time—a development that could lead to the creation of ...

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 ...

Babies born with low birth weight (less than 2.5 kg) are 20 times more likely to die. They are also more likely to develop neurological and cardiovascular diseases, diabetes, and growth problems later ...