Researchers sought to determine an effective approach to predict postembolization fever in patients undergoing TACE.

Recent advances in machine learning have significantly enhanced the diagnosis and prediction of thyroid diseases. By integrating diverse algorithms including ensemble methods, neural networks, and ...

COMET, a novel machine learning framework, integrates EHR data and omics analyses using transfer learning, significantly enhancing predictive modeling and uncovering biological insights from small ...

Medical researchers at Mass General Brigham say the self-supervised foundational model can identify inherent features from ...

Can deep learning catch chronic illness before symptoms show? This article explores how time-aware neural networks are reshaping early detection and care planning for conditions like diabetes and COPD ...

A Stanford-led study published in Nature on Feb. 26 found that age-related changes witnessed in diseases like Alzheimer’s may be related to a relatively untapped area of research in the brain. The ...

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 ...

FIU Researchers are training AI to detect heart conditions, like aortic stenosis and heart failure, by analyzing heart sound data to improve early diagnosis and risk prediction. The future of heart ...

The Opioid Risk Tool for Opioid Use Disorder may help identify patients with chronic noncancer pain at increased risk for OUD ...

Cardiovascular disease continues to be the leading cause of death worldwide. To save lives, constantly improving diagnostic and risk assessments is ...

Cancer, Alzheimer’s, and other diseases follow a pathway in the human body. It starts at the molecular and cellular levels, and through a series of complex interactions can lead to the development and ...