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  • April 2020
  • Article
  • Biostatistics

Regulatory Oversight, Causal Inference, and Safe and Effective Health Care Machine Learning

By: Ariel Dora Stern and W. Nicholson Price, II
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Abstract

In 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.

Keywords

Machine Learning; Causal Inference; Health Care and Treatment; Safety; Governing Rules, Regulations, and Reforms

Citation

Stern, 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.
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More from the Authors
  • Maven Clinic: Women's Health in the Digital Age By: Ariel D. Stern and Sarah Mehta
  • Aidoc: Building a Hospital-Centric AI Platform By: Ariel D. Stern and Susan Pinckney
  • Tepid Uptake of Digital Health Technologies in Clinical Trials by Pharmaceutical and Medical Device Firms By: Caroline Marra and Ariel D. Stern
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