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Neonatal Medicine and Machine Learning: Big Opportunities for Small Patients
March 8th, 2023 @ 1:00 pm - 2:00 pm
The Department of Epidemiology Seminar Series
Speaker:
Andrew L. Beam, PhD
Assistant Professor, Department of Epidemiology
Harvard T.H. Chan School of Public Health
Abstract :Infants born prematurely (i.e., before 37 weeks’ gestation) who are admitted to neonatal intensive care unit (NICU) experience some of the highest levels of morbidity and mortality of any pediatric population. Now, with the availability of large sources of healthcare data from insurance claims databases and electronic health records, there is an opportunity to better understand this vulnerable population and improve outcomes using data-driven approaches. In this talk, I will outline opportunities for machine learning in perinatal and neonatal medicine. I will provide an overview of the core challenges in this area and present some recent work using machine learning and causal inference to address these challenges. Finally, I will conclude with an overview of promising future directions where machine learning researchers may contribute to this important medical domain.
Open to the public.