{"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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.015259,0.0008629354,0.000746667,0.003064761,0.0001868959,0.0009498292,0.0004315184,0.0006603465,0.0004252775],"category_scores_gemma":[0.02726488,0.0001774361,0.0008749731,0.001148933,0.000578067,0.001139974,0.000683478,0.0005973049,0.0001388313],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003931693,"about_ca_system_score_gemma":0.0004477544,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0004288939,"about_ca_topic_score_gemma":0.0004245512,"domain_scores_codex":[0.9918914,0.005560128,0.0005108395,0.0006131395,0.001279943,0.0001445675],"domain_scores_gemma":[0.9695565,0.02453136,0.002296217,0.001034491,0.002070115,0.0005113255],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.002828261,0.0005111676,0.8519027,0.0003201529,0.001326931,0.0001115037,0.0001978728,0.01297413,0.001275924,0.0008220831,0.0003169358,0.1274123],"study_design_scores_gemma":[0.0003859118,0.008234341,0.6619433,0.000235258,0.001140862,0.001119653,0.000528735,0.3171596,0.003400639,0.004221498,0.001495164,0.0001350828],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9574088,0.005972185,0.03457896,0.0002308348,0.00009306047,0.0001342899,0.000221522,0.00006935209,0.001291007],"genre_scores_gemma":[0.9897805,0.0005799569,0.009203263,0.00004421816,0.00006605808,0.000043315,0.0001657125,0.000009662377,0.0001072543],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.015259,"threshold_uncertainty_score":0.08069825,"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."}}