| Literature DB >> 31742358 |
Ariel Dora Stern1, W Nicholson Price2,3.
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: Causal inference; Device regulation; FDA; Machine learning; Software as a medical device
Mesh:
Year: 2020 PMID: 31742358 DOI: 10.1093/biostatistics/kxz044
Source DB: PubMed Journal: Biostatistics ISSN: 1465-4644 Impact factor: 5.899