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

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Do no harm: a roadmap for responsible machine learning for health careJenna Wiens # 1, Suchi Saria # 2 3 4, Mark Sendak 5, Marzyeh Ghassemi 6 7 8, Vincent X Liu 9, Finale Doshi-Velez 10, Kenneth Jung 11, Katherine Heller 12 13, David Kale 14, Mohammed Saeed 15, Pilar N Ossorio 16, Sonoo Thadaney-Israni 17, Anna Goldenberg # 18 19 20 21

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PMID: 31427808 1 comment on PubPeer (by: Dicranocara Inexpectata)
DOI: 10.1038/s41591-019-0548-6

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[size=1.8]Author Correction: Do no harm: a roadmap for responsible machine learning for health care.[size=1.4]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.Nat Med. 2019 Oct;25(10):1627. doi: 10.1038/s41591-019-0609-x.PMID: 31537911

Abstract

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).

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