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, considering factors such as data heterogeneity, model ...

A study published in JCO Clinical Cancer Informatics demonstrates that machine learning models incorporating patient-reported outcomes and wearable sensor data can predict which patients with non–small cell lung cancer are most at risk of needing urgent care during treatment.

Let’s look back at the surprisingly long history of AI innovation in ad tech, and where I see automation taking us next.

Sleep disturbances are a key contributor to agitation. Poor sleep quality, characterized by frequent awakenings, insomnia, and fragmented rest, affects up to half of dementia patients in advanced stages.

Using a cohort of more than 33,000 Chinese patients, investigators comprehensively analyzed urinary stone composition.

A machine learning tool’s analysis of over 140,000 factors outperforms a fracture liaison service approach to fracture risk prediction, but its clinical utility remains uncertain.

A breakthrough in nuclear physics at Florida Polytechnic University has created an advanced machine learning model that predicts nuclear binding energies with unprecedented accuracy, helping scientists better understand the building blocks of matter.