{"id":"W4225504827","doi":"10.2196/36997","title":"Noninvasive Diagnosis of Nonalcoholic Steatohepatitis and Advanced Liver Fibrosis Using Machine Learning Methods: Comparative Study With Existing Quantitative Risk Scores","year":2022,"lang":"en","type":"article","venue":"JMIR Medical Informatics","topic":"Liver Disease Diagnosis and Treatment","field":"Medicine","cited_by":16,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"National Center for Advancing Translational Sciences","keywords":"Cirrhosis; Nonalcoholic fatty liver disease; Medicine; Internal medicine; Fibrosis; Steatosis; Liver biopsy; Hepatocellular carcinoma; Steatohepatitis; Fatty liver; Gastroenterology; Alanine transaminase; Machine learning; Algorithm; Biopsy; Artificial intelligence; Computer science; Disease","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":[0.0005155819,0.0002568775,0.0007426083,0.0001893414,0.0004122474,0.00002365969,0.0001123305,0.00004502236,0.0003238063],"category_scores_gemma":[0.0002952465,0.0001912695,0.00009286338,0.0004048071,0.0002416064,0.0002190532,0.0002860425,0.0005184581,0.000002796081],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001424797,"about_ca_system_score_gemma":0.00020968,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0007528859,"about_ca_topic_score_gemma":0.00009092355,"domain_scores_codex":[0.9974222,0.0004577558,0.0006574233,0.0001986739,0.001008939,0.0002550231],"domain_scores_gemma":[0.9971837,0.001505221,0.0006104556,0.0001932321,0.0001899424,0.0003174781],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0005367685,0.001696148,0.9184729,0.0003486917,0.000939334,0.0001736617,0.06763029,0.0006820733,0.000007142819,0.0001032539,0.00002575738,0.009383918],"study_design_scores_gemma":[0.01974341,0.02681007,0.4478199,0.002303618,0.003543549,0.0003569663,0.2469444,0.2485586,0.002152377,0.00004991316,0.0007901134,0.0009270957],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9963152,0.001182228,0.0005586286,0.00002836568,0.0000316271,0.001484939,0.0001537683,0.00003862472,0.0002065596],"genre_scores_gemma":[0.9456947,0.0004919369,0.05290734,0.0001162893,0.00001531061,0.0006670484,0.00007671357,0.00002011877,0.0000105583],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.4706531,"threshold_uncertainty_score":0.7799744,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.07082853940036576,"score_gpt":0.3957733190270052,"score_spread":0.3249447796266395,"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."}}