Do no harm: a roadmap for responsible machine learning for health care.

Published

Journal Article (Review)

Interest in machine-learning applications within medicine has been growing, but few studies have progressed to deployment in patient care. We present a framework, context and ultimately guidelines for accelerating the translation of machine-learning-based interventions in health care. To be successful, translation will require a team of engaged stakeholders and a systematic process from beginning (problem formulation) to end (widespread deployment).

Full Text

Duke Authors

Cited Authors

  • Wiens, J; Saria, S; Sendak, M; Ghassemi, M; Liu, VX; Doshi-Velez, F; Jung, K; Heller, K; Kale, D; Saeed, M; Ossorio, PN; Thadaney-Israni, S; Goldenberg, A

Published Date

  • September 2019

Published In

Volume / Issue

  • 25 / 9

Start / End Page

  • 1337 - 1340

PubMed ID

  • 31427808

Pubmed Central ID

  • 31427808

Electronic International Standard Serial Number (EISSN)

  • 1546-170X

International Standard Serial Number (ISSN)

  • 1078-8956

Digital Object Identifier (DOI)

  • 10.1038/s41591-019-0548-6

Language

  • eng