{"id":"W3087893815","doi":"10.1146/annurev-biodatasci-092820-114757","title":"Ethical Machine Learning in Healthcare","year":2021,"lang":"en","type":"article","venue":"Annual Review of Biomedical Data Science","topic":"Artificial Intelligence in Healthcare and Education","field":"Medicine","cited_by":479,"is_retracted":false,"has_abstract":true,"ca_institutions":"Vector Institute","funders":"National Institute on Minority Health and Health Disparities","keywords":"Health care; Pipeline (software); Ethical issues; Selection (genetic algorithm); Frame (networking); Healthcare system","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":["metaresearch"],"consensus_categories":[],"category_scores_codex":[0.06553072,0.0005211338,0.0009881723,0.001433642,0.004018919,0.01095027,0.0018216,0.01201605,0.004743126],"category_scores_gemma":[0.1111826,0.0004199058,0.0007542342,0.001283199,0.03392461,0.01144494,0.007351228,0.01494956,0.001124146],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.006368436,"about_ca_system_score_gemma":0.01273539,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002196424,"about_ca_topic_score_gemma":0.002079176,"domain_scores_codex":[0.9289199,0.05395311,0.002291261,0.003068164,0.00959992,0.002167666],"domain_scores_gemma":[0.8982011,0.08200955,0.003999,0.006649499,0.006120124,0.003020798],"domain_codex":null,"domain_gemma":"methods","domain_candidate":"methods","domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.00001608896,0.0000229559,0.000591026,0.000178008,0.00001786165,0.00008268174,0.001471689,0.0005679764,0.00006092669,0.9218505,0.02716888,0.04797144],"study_design_scores_gemma":[0.00001213655,0.00001970791,0.0003176772,0.0008600331,0.000007610244,0.0001753261,0.0007456582,0.000810432,0.0001321756,0.8835843,0.1133157,0.00001928057],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"commentary","genre_gemma":"review","genre_scores_codex":[0.003625997,0.04590939,0.03522015,0.8741505,0.002875031,0.00005751645,0.0000714591,0.00005300675,0.03803705],"genre_scores_gemma":[0.4937366,0.09224717,0.03840081,0.3408519,0.01936463,0.0005800843,0.0001879933,0.0002327188,0.01439811],"genre_candidate":"review","genre_consensus":null,"teacher_disagreement_score":0.9344693,"threshold_uncertainty_score":0.3465637,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.192406255687194,"score_gpt":0.518899363750473,"score_spread":0.3264931080632789,"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."}}