Researchers at MUSC Hollings Cancer Center have developed a machine learning tool to identify cancer patients who may be at high risk for financial toxicity—the financial stress and hardship that can ...
A new research published in the Journal of the American Medical Association revealed that a machine learning model which ...
Enhancing Readability of Lay Abstracts and Summaries for Urologic Oncology Literature Using Generative Artificial Intelligence: BRIDGE-AI 6 Randomized Controlled Trial We trained and tested ML systems ...
Physiologically Based Pharmacokinetic Model to Assess the Drug-Drug-Gene Interaction Potential of Belzutifan in Combination With Cyclin-Dependent Kinase 4/6 Inhibitors A total of 14,177 patients were ...
A machine-learning model developed by Weill Cornell Medicine investigators may provide clinicians with an early warning of a complication that can occur late in pregnancy. Preeclampsia is a sudden ...
Two complementary predictors (DAAE-M and ELIE) estimate individualized 5-year progression risk using routine clinical data, extending the prior DAAE framework beyond static baseline risk. Registry ...
illustrating the comprehensive zero-shot benchmark of 19 universal machine learning interatomic potentials and the dominant impact of training data composition for surface energy prediction. A ...
A machine learning model uses cloud type and cloud cover to predict rapid changes in surface solar irradiance, including short-term “ramp” events that affect grid stability. When tested across 15 ...
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