A machine learning-based heart disease prediction model (ML-HDPM) that uses various combinations of information and numerous recognized categorization methods.

Discover how machine learning shows high accuracy for HIV prediction but needs better validation before use in STI clinical ...

A machine learning model bests traditional methods for predicting cirrhosis mortality among hospitalized patients.

Dr. Shipra Arya, Stanford vascular surgeon, receives $300,000 AHA award to develop an automated deep learning–based ...

Using a cohort of more than 33,000 Chinese patients, investigators comprehensively analyzed urinary stone composition.

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.

Our findings suggest that integrating machine learning into traditional statistical methods can provide more accurate and generalizable models for disease risk prediction.

Melkani envisions using deep learning-assisted studies to explore cardiac mutation models and other small animal models, such as zebrafish and mice. “Additionally, our techniques could be adapted for ...

Stanford University researchers developed a machine learning-based method capable of diagnosing multiple diseases using B cell and T cell receptor sequences. The model, called Machine learning for ...