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 ...
We found four breast cancer risk prediction models that had been tested enough times to evaluate in detail. These were the Gail, Tyrer-Cuzick, BOADICEA, and BRCAPRO models. The BOADICEA model was one ...
New developments in artificial intelligence could use sleep data to predict disease risk, a new study suggests. Stanford Medicine researchers have developed an AI model trained on nearly 600,000 hours ...
Researchers have developed artificial intelligence (AI) models that can scrutinize electronic health records (EHR) and electrocardiograms to identify individuals in the general population at elevated ...
Strong discrimination for total CVD was observed with the base PREVENT equation, with C indexes of 0.764 (White), 0.773 (Asian), and 0.757 (Native Hawaiian and Other Pacific Islander). Marked ...
Deep Learning–Based Body Composition Analysis for Outcome Prediction in Relapsed/Refractory Diffuse Large B-Cell Lymphoma: Insights From the LOTIS-2 Trial We analyzed electronic health record data of ...
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