{"id":"W2954731382","doi":"10.1177/0840470419843831","title":"Healthcare uses of artificial intelligence: Challenges and opportunities for growth","year":2019,"lang":"en","type":"article","venue":"Healthcare Management Forum","topic":"Artificial Intelligence in Healthcare and Education","field":"Medicine","cited_by":99,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University; Université de Montréal; Montreal Clinical Research Institute","funders":"","keywords":"Health care; Inefficiency; Transparency (behavior); Medical diagnosis; Artificial intelligence; Institution; Computer science; Data science; Knowledge management; Medicine; Computer security; Political science","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":[0.06813506,0.000706057,0.001025027,0.002135883,0.005922234,0.02451433,0.002790702,0.01251925,0.006167481],"category_scores_gemma":[0.05425429,0.0005134299,0.0007135131,0.00239853,0.04071737,0.0318637,0.01055856,0.01530287,0.001438273],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.005665026,"about_ca_system_score_gemma":0.01094169,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001260278,"about_ca_topic_score_gemma":0.001529462,"domain_scores_codex":[0.9616358,0.02624544,0.001462793,0.001549203,0.00689955,0.002207132],"domain_scores_gemma":[0.8769572,0.09647414,0.003366149,0.006765228,0.01019851,0.006238747],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00003028063,0.00006812452,0.0006016669,0.0002862706,0.00001712377,0.0001945661,0.006270362,0.0005934655,0.000253663,0.8514341,0.05067215,0.08957826],"study_design_scores_gemma":[0.00001292021,0.00003084725,0.000267515,0.0006980014,0.000005055243,0.0002319752,0.007177304,0.001180568,0.0001615465,0.7554721,0.2347286,0.00003343781],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"commentary","genre_gemma":"empirical","genre_scores_codex":[0.002401935,0.02339808,0.006918761,0.9448159,0.001533665,0.00001757577,0.00002359309,0.00004336603,0.02084715],"genre_scores_gemma":[0.5575497,0.1456081,0.05566378,0.1943204,0.02595906,0.0004057803,0.0001462074,0.0003454619,0.02000151],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.06813506,"threshold_uncertainty_score":0.360337,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.3274032927124367,"score_gpt":0.4174549312044393,"score_spread":0.0900516384920026,"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."}}