An automated machine-learning program developed by researchers from Edith Cowan University (ECU) in conjunction with the University of Manitoba has been able to identify potential cardiovascular ...

Risk factors for cardiovascular disease have been formally identified for over six decades.

UC Berkeley researchers trained AI to detect hidden warning signs of sudden cardiac death in routine ECG tests, according to ...

Each year in the U.S., more than 300,000 people die from sudden cardiac arrest, a condition in which the heart's electrical ...

If millions of Americans no longer qualify for a statin or a blood pressure medication based on a new calculator updated to better predict their risk, that could lead to 107,000 more heart attacks and ...

New research can transform how hospitals triage, risk-stratify, and counsel patients to save lives. Mount Sinai researchers studying a type of heart disease known as hypertrophic cardiomyopathy (HCM) ...

An AI algorithm based only on routine mammogram images plus age can predict a woman’s risk of major cardiovascular disease as well as standard risk assessment methods, finds research published online ...

Following its successful contribution to the American Association of Equine Practitioners-led project focused on locomotion analysis and musculoskeletal injury prediction, Arioneo has announced the ...

New guidelines from the American College of Cardiology and the American Heart Association (ACC/AHA), in collaboration with several other groups, are now available for the perioperative evaluation and ...

An automated machine learning program has been able to identify potential cardiovascular incidents or fall and fracture risks based on bone density scans taken during routine clinical testing. An ...

An automated machine learning program developed by researchers from Edith Cowan University (ECU) in conjunction with the University of Manitoba has been able to identify potential cardiovascular ...