{"id":"W7143771036","doi":"10.71465/ajml3023","title":"Machine Learning in Healthcare: Forecasting Patient Outcomes with Predictive Models","year":2022,"lang":"","type":"article","venue":"American Journal of Machine Learning","topic":"Machine Learning in Healthcare","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Key (lock); Predictive modelling; Health care; Precision medicine; Predictive analytics; Patient care","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":[0.005746641,0.001148452,0.001211927,0.001711909,0.0004472732,0.002373339,0.001368082,0.001588016,0.001130534],"category_scores_gemma":[0.02556135,0.0004089021,0.0007539457,0.002334662,0.0007202313,0.002424264,0.0013151,0.003073677,0.0005309365],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001162629,"about_ca_system_score_gemma":0.001389813,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.008037738,"about_ca_topic_score_gemma":0.00532615,"domain_scores_codex":[0.9978982,0.001343284,0.00009335931,0.0002237291,0.0003508239,0.00009057562],"domain_scores_gemma":[0.9915271,0.006991362,0.0004827906,0.0003716999,0.0004663987,0.000160503],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0002685902,0.0002592107,0.02894078,0.0003336344,0.0002653502,0.0001579745,0.0002253192,0.6717492,0.0004607001,0.03039289,0.0119256,0.2550207],"study_design_scores_gemma":[0.00001645457,0.00005416881,0.001259864,0.0001174723,0.00003070662,0.00003850761,0.00004930706,0.9535927,0.0002307816,0.04275275,0.00183331,0.00002392645],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.0760445,0.02019344,0.8545787,0.03627347,0.0009853881,0.0002275781,0.001748518,0.001408889,0.00853946],"genre_scores_gemma":[0.819029,0.01322248,0.1608109,0.001862689,0.001514502,0.0002608683,0.001507933,0.0000983564,0.001693235],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.008037738,"threshold_uncertainty_score":0.03039151,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02086631644938547,"score_gpt":0.267366337294894,"score_spread":0.2465000208455085,"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."}}