McGill University researchers have developed a new tool to identify heart disease risk in women earlier in life.

A collaborative project between the University of Melbourne and RMIT has developed a thermal-imaging artificial intelligence ...

A deep learning-based AKI risk assessment strategy triggered early nephrology recommendations, but low adherence and limited ...

Overview: Healthcare innovation combines AI, IoT, data analytics, and software development to solve real-world medical and ...

A machine learning model improves prediction of type 1 diabetes risk compared with a conventional genetic risk model, particularly in people without high-risk human leukocyte antigen haplotypes.

Artificial intelligence is transforming healthcare, supporting clinicians in diagnosis, prognosis, treatment planning, and ...

Researchers developed a two-stage machine learning framework that detected diabetes and classified records as prediabetes, ...

According to The Danish Diabetes Association, about 100,000 Danes are unaware that they have type 2 diabetes, and ...

The current MA risk adjustment model has shortcomings, both in predictive accuracy and payment equity across the Medicare ...

A large study found specific gut microbes associated with future type 2 diabetes years before diagnosis. The findings suggest ...

BACKGROUND: Screening for atrial fibrillation (AF) on the basis of AF risk may be more effective. We aimed to develop, ...

Noninvasive WDs coupled with machine learning (ML) techniques have the potential to understand and conclude meaningful information from the gathered data and provide clinically meaningful advanced ...