A study of a new AI model examining 30 years of routine electronic health records (EHR) data could improve screening for primary aldosteronism, a leading cause of high blood pressure that is often ...
MASLD is prevalent in T2DM patients, with a 65% occurrence rate, and poses a higher risk for severe liver diseases. The study analyzed 3,836 T2DM patients, identifying key predictors like BMI, ...
Routine water quality monitoring already generates large volumes of physicochemical data – turbidity, temperature, dissolved oxygen – but converting that into an early warning for microbial ...
Objective This study reviewed the current state of machine learning (ML) research for the prediction of sports-related injuries. It aimed to chart the various approaches used and assess their efficacy ...
Cost-Effectiveness of Maintaining Higher Stem-Cell Collection Thresholds in the Chimeric Antigen Receptor T-Cell Era for Multiple Myeloma Predicting severe adverse events (SAEs) in oncology is ...
Bottom line: A machine learning model that analyzes patient demographics, electronic health record data, and routine blood test results predicted a patient's risk of hepatocellular carcinoma (HCC), ...
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