Machine learning for the prediction of urosepsis using electronic health record data

ML modeling to predict urosepsis risk using UCLA EHR data. We show that Random forest outperforms baseline APR.

Developed machine learning models to predict urosepsis risk from EHR data in outpatient UTI patients. Random forest achieved significant improvement.

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