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 ...

There are more candidates on the waitlist for a liver transplant than there are available organs, yet about half the time a match is found with a donor who dies after cardiac arrest following ...

Machine learning algorithms may accurately predict inborn errors of immunity (IEI) in children with persistently low serum IgE.

Researchers develop radiomics-based predictive models to assess the likelihood of progressively refractory intracranial hypertension leading to secondary DC. The multiomic model, which incorporated ...

New paired studies from the University of Minnesota Twin Cities show that machine learning can improve the prediction of ...

A machine learning model for prediction of preeclampsia risk using routinely collected data was feasible among pregnancies in ...

Reliable and scalable water level prediction is crucial in hydrology for effective water resources management, especially ...

A new study suggests that lenders may get their strongest overall read on credit default risk by combining several machine learning models rather than relying on a single algorithm. The researchers ...

Characterized by weakened or damaged heart musculature, heart failure results in the gradual buildup of fluid in a patient's lungs, legs, feet, and other parts of the body. The condition is chronic ...

A newly developed machine learning model may be able to predict intimate partner violence in patients before they seek help.