{"id":"W4404414807","doi":"10.1093/jamiaopen/ooae108","title":"Addressing ethical issues in healthcare artificial intelligence using a lifecycle-informed process","year":2024,"lang":"en","type":"article","venue":"JAMIA Open","topic":"Artificial Intelligence in Healthcare and Education","field":"Medicine","cited_by":18,"is_retracted":false,"has_abstract":true,"ca_institutions":"Simon Fraser University","funders":"U.S. National Library of Medicine; National Human Genome Research Institute; National Institutes of Health","keywords":"Deliberation; System lifecycle; Context (archaeology); Process (computing); Engineering ethics; Knowledge management; Health care; Application lifecycle management; Management science; Computer science; Engineering; Political science; Politics","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":[],"consensus_categories":[],"category_scores_codex":[0.1567878,0.001454165,0.0008967081,0.005443058,0.01059947,0.02234106,0.003903822,0.008292292,0.00423609],"category_scores_gemma":[0.1334611,0.001162397,0.002228756,0.003680976,0.04069437,0.02040751,0.01818729,0.0110869,0.00127138],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.01650174,"about_ca_system_score_gemma":0.05800465,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00400222,"about_ca_topic_score_gemma":0.005301822,"domain_scores_codex":[0.8155283,0.1556016,0.006539324,0.0038716,0.01581133,0.002647849],"domain_scores_gemma":[0.7909783,0.1561072,0.01253753,0.01538032,0.02085961,0.004137019],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.00004812409,0.0001794941,0.002071166,0.000973116,0.00005516564,0.0006867925,0.08242507,0.003613407,0.0009164754,0.8289397,0.005318331,0.07477315],"study_design_scores_gemma":[0.00005351377,0.00008711917,0.0006250197,0.003051147,0.00004036932,0.0005535539,0.03462815,0.00759041,0.001459589,0.8366913,0.1151328,0.00008707549],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.02291398,0.003623043,0.7838202,0.08761857,0.0005078604,0.00559917,0.0001538931,0.0003179804,0.09544534],"genre_scores_gemma":[0.3078647,0.002812309,0.6746945,0.004639739,0.0002268567,0.003286747,0.0002138228,0.0001297133,0.006131553],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.1567878,"threshold_uncertainty_score":0.829183,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.5427085924048283,"score_gpt":0.6096807545039306,"score_spread":0.06697216209910228,"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."}}