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The research team developed and tested algorithms that can predict postoperative adverse outcomes with a high degree of accuracy.
This research applied machine learning to develop a model predicting surgical cancellations among pediatric patients, and found the feasibility in using these algorithms as a cost-effective quality-improvement measure.