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

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

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

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

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

The study also highlights the limitations of relying on body mass index (BMI) as a proxy for metabolic health.

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 ...

Background Early graft failure within 90 postoperative days is the leading cause of mortality after heart transplantation. Existing risk scores, based on linear regression, often struggle to capture ...

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

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 ...