Stern, ArielPrice, W Nicholson2021-11-192020-04Stern, Ariel Dora, and W. Nicholson Price, II. "Regulatory Oversight, Causal Inference, and Safe and Effective Health Care Machine Learning." Biostatistics 21, no. 2 (April 2020): 363–367.1465-4644https://nrs.harvard.edu/URN-3:HUL.INSTREPOS:37370007In recent years, the applications of Machine Learning (ML) in the health care delivery setting have grown to become both abundant and compelling. Regulators have taken notice of these developments and the U.S. Food and Drug Administration (FDA) has been engaging actively in thinking about how best to facilitate safe and effective use. Although the scope of its oversight for software-driven products is limited, if FDA takes the lead in promoting and facilitating appropriate applications of causal inference as a part of ML development, that leadership is likely to have implications well beyond regulated products.en-USStatistics, Probability and UncertaintyGeneral MedicineStatistics and ProbabilityJournal Article2021-11-1910.1093/biostatistics/kxz044