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This research prospectively evaluated a machine learning algorithm that identifies candidates for neurologic surgery to control epilepsy.
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.