Insulin resistance - when the body doesn't properly respond to insulin, a hormone that helps control blood glucose levels - ...

Machine learning for health data science, fuelled by proliferation of data and reduced computational costs, has garnered ...

A powerful artificial intelligence (AI) tool could give clinicians a head start in identifying life-threatening complications ...

A recent study suggests that a freely available AI tool could help predict dangerous complications after stem cell transplants.

Among patients with chronic noncancer pain, a novel machine learning model effectively predicts opioid use disorder risk.

Postpartum depression (PPD) affects up to 15 percent of individuals after childbirth. Early identification of patients at risk of PPD could improve proactive mental health support. Researchers ...

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 ...

MASLD is prevalent in T2DM patients, with a 65% occurrence rate, and poses a higher risk for severe liver diseases. The study analyzed 3,836 T2DM patients, identifying key predictors like BMI, ...

An interdisciplinary team of researchers has developed a machine learning framework that uses limited water quality samples to predict which inorganic pollutants are likely to be present in a ...

The authors analyze the interest rate risk in the banking book regulations, arguing that financial institutions must develop robust models for forecasting ...