{"id":"W4210844307","doi":"10.1007/s12072-022-10303-0","title":"Conventional and artificial intelligence-based imaging for biomarker discovery in chronic liver disease","year":2022,"lang":"en","type":"review","venue":"Hepatology International","topic":"Liver Disease Diagnosis and Treatment","field":"Medicine","cited_by":48,"is_retracted":false,"has_abstract":false,"ca_institutions":"McGill University Health Centre; McGill University","funders":"National Institute of Allergy and Infectious Diseases; National Cancer Institute; National Institutes of Health; Institut Universitaire de France; Université de Strasbourg; Institut National de la Santé et de la Recherche Médicale; Agence Nationale de la Recherche; Monique Weill-Caulier Trust; National Institute of Diabetes and Digestive and Kidney Diseases; U.S. Department of Defense","keywords":"Medicine; Cirrhosis; Hepatology; Chronic liver disease; Biomarker; Imaging biomarker; Magnetic resonance imaging; Liver disease; Elastography; Steatosis; Hepatocellular carcinoma; Radiology; Internal medicine; Pathology; Intensive care medicine; Ultrasound","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":[0.001145818,0.00101228,0.002069812,0.002641786,0.0001990009,0.001410379,0.0009693067,0.001303494,0.00282687],"category_scores_gemma":[0.001634196,0.0003337649,0.0009191753,0.002557111,0.0005977229,0.001382325,0.0007406708,0.001986918,0.001029221],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005790443,"about_ca_system_score_gemma":0.001044195,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001446875,"about_ca_topic_score_gemma":0.002248138,"domain_scores_codex":[0.9997078,0.00006897886,0.00004471275,0.00005073543,0.0001069047,0.00002087484],"domain_scores_gemma":[0.9991762,0.0005688748,0.000082345,0.00001824451,0.0001282994,0.00002607749],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"systematic_review","study_design_scores_codex":[0.0001016384,0.00007866111,0.0001950554,0.02844932,0.0002893216,0.0001351065,0.00003652312,0.00053473,0.001003341,0.004354331,0.01477429,0.9500477],"study_design_scores_gemma":[0.00009612395,0.0003658846,0.002123024,0.01677833,0.001006348,0.001654276,0.0001076679,0.0009679905,0.001503941,0.008996925,0.9663134,0.00008613834],"study_design_candidate":"systematic_review","study_design_consensus":null,"genre_codex":"review","genre_gemma":"review","genre_scores_codex":[0.00005694691,0.9991428,0.0001786874,0.000151381,0.00007799338,0.000004520271,0.00001439849,0.000004114883,0.0003691654],"genre_scores_gemma":[0.0005955389,0.9985602,0.0003316692,0.000170372,0.0001300949,0.00000678978,0.00002299206,9.754796e-7,0.0001814251],"genre_candidate":"review","genre_consensus":"review","teacher_disagreement_score":0.00282687,"threshold_uncertainty_score":0.009456813,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.118439626656096,"score_gpt":0.3888501118738593,"score_spread":0.2704104852177633,"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."}}