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A machine learning-based clinical decision support system to identify prescriptions with a high risk of medication error.

Journal of the American Medical Informatics Association : JAMIA 32984901
OBJECTIVE: To improve patient safety and clinical outcomes by reducing the risk of prescribing errors, we tested the accuracy of a hybrid clinical decision support system in prioritizing prescription checks.
Decision Support Systems, Clinical Expert Systems Hospitals, Voluntary Humans Machine Learning Medical Order Entry Systems Medication Errors Paris Patient Safety Pharmacists Prescriptions ROC Curve
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