{"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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005863487,0.0002149226,0.0004667527,0.0003477549,0.0001415754,0.00001763684,0.000114617,0.0001594763,0.00004547086],"category_scores_gemma":[0.00005545746,0.0002069969,0.0001066325,0.0001372917,0.0001056265,0.0001333432,0.00007824242,0.0001656954,0.00002150555],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00009981331,"about_ca_system_score_gemma":0.0001638275,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0005145822,"about_ca_topic_score_gemma":0.0003507838,"domain_scores_codex":[0.9977741,0.00007654473,0.000804511,0.0004588055,0.000323815,0.0005622727],"domain_scores_gemma":[0.99845,0.0001856488,0.0002212193,0.0003984618,0.0004810724,0.0002636029],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"qualitative","study_design_scores_codex":[0.0002439001,0.00009488975,0.003011674,0.00718081,0.00004165459,0.000004305341,0.00126562,8.00825e-7,0.000008814958,0.3985119,0.0003504303,0.5892853],"study_design_scores_gemma":[0.0003658147,0.009766939,0.01452607,0.003823459,0.0003268911,0.00008041593,0.4948592,0.002021794,0.009315275,0.3951725,0.06853675,0.001204885],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"commentary","genre_gemma":"empirical","genre_scores_codex":[0.3251109,0.02552397,0.002557588,0.6314249,0.002490648,0.007694113,0.00007912172,0.0002391783,0.004879557],"genre_scores_gemma":[0.9676202,0.02608973,0.001616353,0.003576474,0.0001802555,0.0002112042,0.00006408494,0.0000388284,0.0006028576],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.6425093,"threshold_uncertainty_score":0.8441089,"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."}}