Predicting intra‐operative and postoperative consequential events using machine‐learning techniques in patients undergoing robot‐assisted partial nephrectomy: a Vattikuti Collective Quality Initiative database study

Abstract

The performance of the ML models in the present study was encouraging. Further validation in a multi-institutional clinical setting with larger datasets would be necessary to establish their clinical value. ML models can be used to predict significant events during and after surgery with good accuracy, paving the way for application in clinical practice to predict and intervene at an opportune time to avert complications and improve patient outcomes.

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