Key result
Machine learning models show promise in predicting postoperative complications after major abdominal surgery, but clinical implementation is currently limited by poor external validation, lack of transparency, and low practical applicability.
Why the study?
Postoperative complications substantially impact outcomes despite technological advances, but multiple issues challenge the development and clinical implementation of machine learning models for risk prediction.
Do machine learning models improve the prediction of postoperative complications in patients undergoing major abdominal surgery compared to conventional models?
Do machine learning models improve the prediction of postoperative complications in patients undergoing major abdominal surgery compared to conventional models?
While machine learning models hold promise for predicting postoperative complications after major abdominal surgery, significant barriers regarding transparency, external validation, and clinical acceptance must be overcome before widespread implementation.
Machine learning models for postoperative risk prediction require external validation before use; leaves open their clinical translation in major abdominal surgery.
Complications after surgery have a major impact on short- and long-term outcomes, and decades of technological advancement have not yet led to the eradication of their risk. The accurate prediction of complications, recently enhanced by the development of machine learning algorithms, has the potential to completely reshape surgical patient management. In this paper, we reflect on multiple issues facing the implementation of machine learning, from the development to the actual implementation of machine learning models in daily clinical practice, providing suggestions on the use of machine learning models for predicting postoperative complications after major abdominal surgery.
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Stam et al. (2023) conducted a review in Postoperative complications after major abdominal surgery. Machine learning prediction models vs. Conventional logistic regression was evaluated on Prediction of postoperative complications. Machine learning models show promise in predicting postoperative complications after major abdominal surgery, but clinical implementation is currently limited by poor external validation, lack of transparency, and low practical applicability.
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