{"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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow","sts","research_integrity"],"consensus_categories":[],"category_scores_codex":[0.006089167,0.001169445,0.002640243,0.002109007,0.002374933,0.0003350791,0.002436113,0.0001220695,0.0001562477],"category_scores_gemma":[0.001507194,0.001067546,0.0005695502,0.004076663,0.0004761826,0.001366506,0.002159451,0.01671199,0.000005334623],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001818491,"about_ca_system_score_gemma":0.001803665,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01639849,"about_ca_topic_score_gemma":0.000420483,"domain_scores_codex":[0.9796868,0.009836158,0.003355866,0.001432762,0.003604753,0.002083651],"domain_scores_gemma":[0.9870379,0.002158685,0.008178741,0.0008105278,0.0008533229,0.0009608167],"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":[0.0007109428,0.0001893937,0.3305223,0.0000627828,0.0001369624,0.0007783836,0.01084887,0.4572694,0.000002192329,0.0002382765,0.00000600062,0.1992345],"study_design_scores_gemma":[0.00243506,0.03185691,0.01466636,0.0005048324,0.00008431533,0.00351617,0.004275053,0.9380788,0.000002906748,0.0003795362,0.003259524,0.0009405766],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7328324,0.01360306,0.1882165,0.06027849,0.002168109,0.001658053,0.00008166189,0.0003943227,0.0007674341],"genre_scores_gemma":[0.9794301,0.0003987307,0.01740167,0.002034114,0.0002044688,0.00005836844,0.00002305921,0.0002257002,0.0002238054],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.4808094,"threshold_uncertainty_score":0.9991775,"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."}}