Machine learning for health data science, fuelled by proliferation of data and reduced computational costs, has garnered considerable interest among researchers. The debate around the use of machine ...

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 ...

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 ...

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

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 ...

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 ...

Dengue is becoming a bigger challenge in many parts of the world, including Latin America, as the factors that influence mosquito-borne disease continue to shift. McCord noted that in the Amazon and ...

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

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 ...

Interpretable AI model could offer new insights into why medicines cause certain side effects, helping to improve future drug safety predictions.