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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.
This research assessed the use of a multi-risk adolescent interactive health assessment screening tool in pediatric primary care settings, which found an increased rate of clinician counseling for endorsed behaviors, but no significant change in reported risk behaviors or patient satisfaction.