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) ...
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 ...
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 ...
A machine-learning algorithm has the capability to identify hospitalized patients at risk for severe sepsis and septic shock using data from electronic health records (EHRs), according to a study ...
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 ...
When people participate in studies of aging, they often want to know what their individual risks of developing dementia from Alzheimer's disease are. Washington University researchers have developed ...
NASHUA, N.H., June 26, 2024 (GLOBE NEWSWIRE) -- iCAD, Inc. (ICAD), a global leader in clinically proven AI-powered cancer detection solutions, today announced it will highlight new research ...
A new algorithm aims to assess the likelihood of defendants being treated unfairly in court. The tool considers details that ought to be immaterial to the ruling — such as the judge’s and defendant’s ...
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 ...
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