A Stanford AI model trained on nearly 600,000 hours of sleep data can assess future risk for dementia, heart disease and more ...

As detailed in a recently released paper, the SleepFM AI model analyzes a comprehensive suite of physiological recordings to ...

This study shows that specific ratios of circulating sphingolipids to steroids can predict the risk of future asthma ...

AI can use sleep data from a single night to identify patterns linked to disease risk years before symptoms appear.

Elevated baseline LDH levels predict worse clinical outcomes in heart failure with reduced ejection fraction and modestly ...

The PCE was developed by the American College of Cardiology and American Heart Association and uses factors such as age, sex, ...

International study of more than 700 participants suggests intrinsic capacity scores offer better predictions than counting ...

A new international study led by researchers from UNSW Sydney's Center for Healthy Brain Aging (CHeBA) has developed the ...

A multimodal sleep foundation model based on polysomnography data can predict the risk for multiple conditions, including dementia.

Chase Markel, a University of Wyoming Ph.D. student from Wheatland, is harnessing artificial intelligence to transform how animal scientists study risk factors for congestive heart failure in cattle.

Please provide your email address to receive an email when new articles are posted on . The model predicted a 12.6% average risk for recurrent disease activity among DMT discontinuers. The model’s AUC ...