{"id":"W4226066893","doi":"10.2196/35293","title":"Comparison of Severity of Illness Scores and Artificial Intelligence Models That Are Predictive of Intensive Care Unit Mortality: Meta-analysis and Review of the Literature","year":2022,"lang":"en","type":"review","venue":"JMIR Medical Informatics","topic":"Sepsis Diagnosis and Treatment","field":"Medicine","cited_by":33,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"National Heart, Lung, and Blood Institute; Northwestern University","keywords":"Medicine; Scopus; Intensive care unit; MEDLINE; Severity of illness; Predictive modelling; Meta-analysis; Intensive care; Intensive care medicine; Systematic review; Emergency medicine; Machine learning; Internal medicine; Computer science","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005381607,0.000345584,0.006145842,0.0002466181,0.0000414125,0.000007360596,0.0002704675,0.0002737733,0.0001657305],"category_scores_gemma":[0.0007876111,0.0001789119,0.001483913,0.001109628,0.0005786591,0.00008743705,0.0003727469,0.0005819105,1.03765e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0000436422,"about_ca_system_score_gemma":0.0003104958,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0000434707,"about_ca_topic_score_gemma":0.00001876833,"domain_scores_codex":[0.9957709,0.0002653831,0.002269541,0.0001714084,0.001390253,0.0001325395],"domain_scores_gemma":[0.9946808,0.0006339945,0.002723177,0.0006581941,0.001159002,0.0001448571],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"systematic_review","study_design_gemma":"meta_analysis","study_design_scores_codex":[0.00004165618,0.000468279,0.002374607,0.6006728,0.09072477,0.000008376608,0.03064558,0.00001031643,2.194549e-8,0.0002743586,0.0001922749,0.2745869],"study_design_scores_gemma":[0.0002699017,0.000580598,0.0006335618,0.1603433,0.7604496,0.00005275547,0.06385131,0.001939368,0.0002344415,0.0002115765,0.01101217,0.0004214218],"study_design_candidate":"meta_analysis","study_design_consensus":null,"genre_codex":"review","genre_gemma":"review","genre_scores_codex":[0.002176261,0.9945873,0.00007546472,0.00008129809,0.00004757083,0.001654566,0.001314856,0.000005040283,0.00005766115],"genre_scores_gemma":[0.03143468,0.9675691,0.00009502365,0.000276347,0.0000103175,0.0001919582,0.0004088731,0.00001134938,0.000002314838],"genre_candidate":"review","genre_consensus":"review","teacher_disagreement_score":0.6697248,"threshold_uncertainty_score":0.7295814,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.4009658761119045,"score_gpt":0.4762346889254576,"score_spread":0.07526881281355313,"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."}}