A novel algorithm based on patient-reported outcome questionnaires stratified patients by disease complexity and effectively identified those at a higher risk of having an acute care visit. Gauging ...

Researchers have developed a new algorithm that can accurately track a patient's level of consciousness, easing strain on clinicians and enabling new treatments. Visit a neurological ICU during a ...

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) ...

A new AI tool developed by researchers from Cedars-Sinai Medical Center can accurately measure plaque deposits in coronary arteries and predict a patient’s risk of suffering a heart attack within five ...

Accurate patient matching across the care continuum is essential for quality and safety. It's also key to driving down healthcare costs by reducing the ordering of duplicative medical tests. But ...

A machine-learning algorithm can use demographic, symptomatic, and clinical data to accurately predict the health-related quality of life (QoL) of patients with kidney stones, new research shows.

ECG denotes electrocardiogram; HCM–, hypertrophic cardiomyopathy negative; and HCM+, hypertrophic cardiomyopathy positive. Mount Sinai researchers studying a type of heart disease known as ...