The authors created a machine learning–based model to identify patients with major depressive disorder in the primary care setting at high risk of frequent emergency department visits, enabling ...

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 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 ...

A study published in mBio, the online open-access journal of the American Society for Microbiology, may help create a test to predict which hospital patients are at the highest risk of developing a ...

Approval last week by U.S. Food and Drug Administration (FDA) clears the path for nationwide use of tools that show the greatest specificity in estimating the risk of ovarian cancer in women with a ...

PARIS, France—Using a simple, automated algorithm can reduce wait times for TAVI without increasing rates of morbidity or mortality, according to a new analysis. “For us, this was drawn out of ...

Researchers at the Johns Hopkins Kimmel Cancer Center and the Department of Gynecology and Obstetrics at the Johns Hopkins University School of Medicine have developed an algorithm to identify ...