A machine learning model incorporating functional assessments predicts one-year mortality in older patients with HF and improves risk stratification beyond established scores. Functional status at ...

Scientists at Université de Montréal and its affiliated Centre de recherche Azrieli du CHU Sainte-Justine have made a major ...

Researchers have found growing evidence that contemporary mammogram imaging combined with AI analysis are able to predict a woman's risk for major cardiovascular events, such as heart attacks and ...

Waist-to-height ratio outperforms BMI in predicting heart disease risk, particularly among people who are not classified as ...

Men face a higher risk of cardiovascular disease earlier than women, so heart health awareness, prevention and early detection are key decades sooner than many may think.

A deep learning model using retinal images obtained during ROP screening may be used to predict diagnosis of BPD and PH.

The healthcare industry is at a crossroads. Advanced analytical technology and operational efficacy converge with strategic ...

New developments in artificial intelligence could use sleep data to predict disease risk, a new study suggests. Stanford Medicine researchers have developed an AI model trained on nearly 600,000 hours ...

A poor night's sleep portends a bleary-eyed next day, but it could also hint at diseases that will strike years down the road. A new artificial intelligence model developed by Stanford Medicine ...

A new global study suggests that a mismatch between two routine blood tests used to assess kidney function may quietly signal elevated risks of kidney failure, heart disease, and death. Credit: ...

Abstract: Heart disease remains one of the leading causes of death worldwide. Effective management and prevention heavily depend on early detection and accurate prediction. However, traditional ...