OCHIN researchers describe project designed to improve risk estimates by combining clinical information with patients’ lived ...

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

Introduction Efficient preventive management of acute exacerbation of chronic obstructive pulmonary disease (COPD) is ...

BACKGROUND: Hypertension induces structural and functional damage in multiple organs. Evidence of subclinical damage ...

The treatment, currently designated HTX-001, is an antisense oligonucleotide, or ASO, that targets Wisper and reduces the ...

A common misperception exists that electrocardiograms (ECGs) simply contain data about heart activity. However, modern ECGs enhanced with artificial intelligence (AI) can contain data about a ...

Abstract: Heart disease remains a leading cause of mortality worldwide, necessitating early and accurate detection to improve patient outcomes. This paper presents a Heart Disease Prediction System ...

Mammograms, which are key to detecting breast cancer, could be paired with artificial intelligence to predict heart disease risk, too. Researchers have developed an AI model that scans mammograms to ...

A tool developed by the American Heart Association (AHA), proven to accurately predict heart disease risk for Americans, can be applied to the global population, a new study led by NYU Langone Health ...

Two complementary predictors (DAAE-M and ELIE) estimate individualized 5-year progression risk using routine clinical data, extending the prior DAAE framework beyond static baseline risk. Registry ...

NEW YORK – Researchers at Mount Sinai have created an analytic tool using machine learning that they say can predict cardiovascular disease risk in millions of patients with obstructive sleep apnea, ...

Polymarket and Kalshi are quickly making deals with news publishers, with potential implications for the regulation of prediction markets. It’s unclear how journalism wins. Are prediction markets ...