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.

Cleveland Clinic and IBM researchers are using quantum computing to tackle one of the most challenging problems in ...

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

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

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

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

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

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

Higher levels of urinary metals such as cadmium, tungsten, uranium, cobalt, copper and zinc are linked to increased cardiovascular disease and mortality in a racially and ethnically diverse U.S.

Gene Solutions, a global biotechnology company focused on accessible and responsible genomics, participated as a Premier ...

Researchers have developed a new AI tool to detect diabetes. Here is how it will work and how it can be used to classify ...

AI pioneer Yann LeCun has raised $1.03 billion (nearly €900 million) and named a new CEO for his new artificial intelligence (AI) startup that will operate partly out of Paris. The French-American ...