In a recent study published in Scientific Reports, researchers developed a machine learning-based heart disease prediction model (ML-HDPM) that uses various combinations of information and numerous ...

Individual prediction uncertainty is a key aspect of clinical prediction model performance; however, standard performance ...

Chronic kidney disease (CKD) constitutes a major global health challenge, affecting millions and often remaining undiagnosed until advanced stages. Recent advances in machine learning have ...

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 ...

Objective To develop and validate a 10-year predictive model for cardiovascular and metabolic disease (CVMD) risk using ...

More than 300 people across academia and industry spilled into an auditorium to attend a BoltzGen seminar on Thursday, Oct.

Breast cancer is a highly heterogeneous malignancy among women worldwide. Traditional prognostic models relying solely on ...

Machine learning is increasingly recognized as a pivotal tool in the evolution of cardiovascular medicine, promising to ...

The predictive role of mammographic breast calcifications in cardiovascular disease among women undergoing breast cancer screening: Insights from a retrospective database analysis of breast cancer ...

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 ...

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 ...