A novel electronic health record-based prediction model successfully identified patients who were at the highest risk of developing type 2 diabetes up to 10 years later. Researchers presented the ...
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 ...
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 ...
An artificial intelligence (AI) model developed by researchers at The University of Texas MD Anderson Cancer Center demonstrated the ability to accurately predict responses to immunotherapy for ...
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 ...
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 ...
Lumo leverages advanced machine learning to reduce calibration time, and flag low-confidence response factor predictions.
Share on Pinterest An AI tool may be able to predict GVHD risk, prompting earlier treatment to prevent complications. Image credit: Victor Bordera/Stocksy An AI-based tool may be able to predict the ...
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 ...
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 ...
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