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Understanding Early Childhood Obesity via Interpretation of Machine Learning Model Predictions., , , and . ICMLA, page 1438-1443. IEEE, (2019)Developing Computable Phenotypes of Pediatric Chronic Conditions in PEDSnet., , , , , , and . AMIA, AMIA, (2017)Building Learning Health Systems to Accelerate Research and Improve Outcomes of Clinical Care in Low- and Middle-Income Countries, , , , , , , , , and 74 other author(s). PLOS Medicine, 13 (4): e1001991 (April 2016)Informatics to support the IOM social and behavioral domains and measures., , , and . J. Am. Medical Informatics Assoc., 22 (4): 921-924 (2015)Prediction of early childhood obesity with machine learning and electronic health record data., , , and . Int. J. Medical Informatics, (2021)Large Databases for Pediatric Research on Children with Autism Spectrum Disorder., , , , , , , , and . J Dev Behav Pediatr, (2018 Feb/Mar 2018)Developing Computable Phenotypes for Pediatric Chronic Conditions in PEDSnet., , , , , , and . CRI, AMIA, (2017)EHR-based Quality Measurement to Reduce Antibiotic Use in Children., , , , , , and . AMIA, AMIA, (2017)Missing data matter: an empirical evaluation of the impacts of missing EHR data in comparative effectiveness research., , , , , , , and . J. Am. Medical Informatics Assoc., 30 (7): 1246-1256 (June 2023)Building Learning Health Systems to Accelerate Research and Improve Outcomes of Clinical Care in Low- and Middle-Income Countries, , , , , , , , , and . PLoS Med, 13 (4): e1001991 (April 2016)