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 based on electronic health record data can provide updated predictions of preeclampsia risk, ...
A machine-learning model developed by Weill Cornell Medicine investigators may provide clinicians with an early warning of a ...
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 ...
Drug discovery is like molecular Tetris. Chemists snap atoms together, adjusting the pieces until everything fits, and suddenly, a molecule makes a promising new medicine. Normally, creating better ...
LCGC International’s interview series on the evolving role of artificial intelligence (AI)/machine learning (ML) in separation science continues with Boudewijn Hollebrands from Unilever Foods R&D, ...
WPI researchers use machine learning and brain scans to identify age- and sex-specific anatomical patterns that predict ...
A new computational method allows modern atomic models to learn from experimental thermodynamic data, according to a ...
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 ...
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