Abstract
Background: Postoperative delirium is a prevalent and disabling mental disorder that occurs regularly in patients undergoing cardiac surgery. Delirium is associated with increased morbidity and mortality as well as a prolonged hospital stay. Identifying patients likely to develop delirium post-extubation at the earliest possible point in time may help to guide treatment decisions. This study compares machine learning models for the prediction of delirium in patients undergoing aorto coronary bypass surgery.
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