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Publications

  1. Validation of a machine learning algorithm for predicting hypoxic ischaemic encephalopathy. Arch Dis Child Fetal Neonatal Ed. 2025 Apr 15. View Abstract

  2. Development and Validation of a Novel Deep Learning Model to Predict Pharmacologic Closure of Patent Ductus Arteriosus in Premature Infants. J Am Soc Echocardiogr. 2025 Apr 11. View Abstract

  3. Artificial intelligence in pediatric medicine: a call for rigorous reporting standards. J Perinatol. 2025 Apr 02. View Abstract

  4. AI models in clinical neonatology: a review of modeling approaches and a consensus proposal for standardized reporting of model performance. Pediatr Res. 2024 Dec 17. View Abstract

  5. Perinatal Factors Associated with Successful Pharmacologic Closure of the Patent Ductus Arteriosus in Premature Infants. Pediatr Cardiol. 2024 Aug 21. View Abstract

  6. Assessment of the clinical knowledge of ChatGPT-4 in neonatal-perinatal medicine: a comparative analysis with ChatGPT-3.5. J Perinatol. 2024 Sep; 44(9):1365-1366. View Abstract

  7. Transforming neonatal care with artificial intelligence: challenges, ethical consideration, and opportunities. J Perinatol. 2024 01; 44(1):1-11. View Abstract

  8. Performance of a Large Language Model on Practice Questions for the Neonatal Board Examination. JAMA Pediatr. 2023 09 01; 177(9):977-979. View Abstract

  9. Artificial intelligence in the neonatal intensive care unit: the time is now. J Perinatol. 2024 01; 44(1):131-135. View Abstract

  10. Health-Related Qualities of Life in School-Aged Children with Bronchopulmonary Dysplasia. J Pediatr. 2023 10; 261:113548. View Abstract

  11. National Needs Assessment of Utilization of Common Newborn Clinical Decision Support Tools. Am J Perinatol. 2024 05; 41(S 01):e1982-e1988. View Abstract

  12. PD(AI): the role of artificial intelligence in the management of patent ductus arteriosus. J Perinatol. 2023 02; 43(2):257-258. View Abstract

  13. Prediction of extubation failure among low birthweight neonates using machine learning. J Perinatol. 2023 02; 43(2):209-214. View Abstract

  14. Machine learning: remember the fundamentals. Pediatr Res. 2023 01; 93(2):291-292. View Abstract

  15. Specificity of International Classification of Diseases codes for bronchopulmonary dysplasia: an investigation using electronic health record data and a large insurance database. J Perinatol. 2021 04; 41(4):764-771. View Abstract

  16. COVID-19: neonatal-perinatal perspectives. J Perinatol. 2021 05; 41(5):940-951. View Abstract

  17. Prenatal Diagnosis of a Ventral Abdominal Wall Defect. Neoreviews. 2020 04; 21(4):e286-e292. View Abstract

  18. Computerized Physician Order Entry in the Neonatal Intensive Care Unit: A Narrative Review. Appl Clin Inform. 2019 05; 10(3):487-494. View Abstract

  19. Antecedents and outcomes of hypothermia at admission to the neonatal intensive care unit. J Matern Fetal Neonatal Med. 2021 Jan; 34(1):66-71. View Abstract

  20. Examining Perceptions of Computerized Physician Order Entry in a Neonatal Intensive Care Unit. Appl Clin Inform. 2017 04 05; 8(2):337-347. View Abstract

  21. Early postnatal illness severity scores predict neurodevelopmental impairments at 10 years of age in children born extremely preterm. J Perinatol. 2017 05; 37(5):606-614. View Abstract

  22. A systematic review of randomized controlled trials for the prevention of bronchopulmonary dysplasia in infants. J Perinatol. 2014 Sep; 34(9):705-10. View Abstract

  23. Predictors of positive cerebrospinal fluid cultures in infants with bacteremia. Pediatr Infect Dis J. 2014 Apr; 33(4):360-5. View Abstract
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