Objective Cardiovascular diseases (CVD) remain the leading cause of mortality globally, necessitating early risk identification to improve prevention and management strategies. Traditional risk ...
Thirty-day mortality of patients with major trauma fell if they received intubation before hospital admission per prediction from a machine learning risk-stratifying model, according to data published ...
A new machine learning model built using a simple and interpretable approach predicts in-hospital death in patients with acute liver failure and reveals top risk drivers.
A machine-learning model developed by Weill Cornell Medicine investigators may provide clinicians with an early warning of a ...
Objective This study reviewed the current state of machine learning (ML) research for the prediction of sports-related injuries. It aimed to chart the various approaches used and assess their efficacy ...
A machine learning model based on electronic health record data can provide updated predictions of preeclampsia risk, ...
Researchers at Mass General Brigham have developed a series of artificial intelligence (AI) tools that uses machine learning to identify individuals who may be at risk for intimate partner violence ...
MedPage Today on MSN
Model could sound the alarm on preeclampsia risk in late pregnancy
How predictions would impact clinical decision-making is another question, expert says ...
MASLD is prevalent in T2DM patients, with a 65% occurrence rate, and poses a higher risk for severe liver diseases. The study analyzed 3,836 T2DM patients, identifying key predictors like BMI, ...
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