{"id":"W2969881216","doi":"10.1038/s41591-019-0548-6","title":"Do no harm: a roadmap for responsible machine learning for health care","year":2019,"lang":"en","type":"review","venue":"Nature Medicine","topic":"Ethics in Clinical Research","field":"Medicine","cited_by":1002,"is_retracted":false,"has_abstract":false,"ca_institutions":"Ontario Brain Institute; SickKids Foundation; Vector Institute; University of Toronto","funders":"Johns Hopkins University","keywords":"Software deployment; Harm; Health care; Psychological intervention; Context (archaeology); Process (computing); Medicine; Computer science; Artificial intelligence; Knowledge management; Process management; Psychology; Business; Nursing; Political science; Software engineering; Social psychology","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.5198019094089994,"score_gpt":0.686093318272577,"score_spread":0.1662914088635776,"validation_status":"score_only:v0-immature-baseline","note":"Baseline scores from an immature model (maturity gate not passed). Scores rank; they never assert a category."}}