{"id":"W4408703677","doi":"10.1109/ipas63548.2025.10924570","title":"Enhancing Fatty Liver Disease Diagnosis Using Deep from Ultrasound Images","year":2025,"lang":"en","type":"article","venue":"","topic":"Liver Disease Diagnosis and Treatment","field":"Medicine","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"Concordia University","funders":"","keywords":"Fatty liver; Ultrasound; Computer science; Disease; Artificial intelligence; Radiology; Medicine; Pathology","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":[0.0006638489,0.0005977466,0.0004357446,0.00079304,0.000125283,0.0006262019,0.0002962301,0.0006599576,0.001057099],"category_scores_gemma":[0.002017824,0.0001974241,0.0004560596,0.0003070061,0.0002021597,0.0005172656,0.0007581652,0.0006084159,0.000376651],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003242633,"about_ca_system_score_gemma":0.000385142,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002841376,"about_ca_topic_score_gemma":0.005507075,"domain_scores_codex":[0.9998155,0.00006782712,0.0000111901,0.00002895804,0.00004283494,0.00003367377],"domain_scores_gemma":[0.9996403,0.0001838264,0.00004210041,0.00003159505,0.00007453973,0.00002755977],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"observational","study_design_scores_codex":[0.001078718,0.0004456634,0.04468881,0.0003209341,0.0002060283,0.00102019,0.0001649823,0.1777948,0.1090929,0.00212001,0.004147397,0.6589196],"study_design_scores_gemma":[0.00003242913,0.0002051453,0.008777449,0.0000555707,0.00005975294,0.0004478518,0.00005486036,0.9599103,0.0256206,0.003008978,0.001799436,0.00002757534],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5918122,0.00247412,0.397701,0.001432071,0.000129007,0.0001307726,0.0008173552,0.00140905,0.004094359],"genre_scores_gemma":[0.9155869,0.0008031693,0.08018898,0.0005306269,0.00006720138,0.00004177471,0.0006862802,0.0000315928,0.002063527],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.002841376,"threshold_uncertainty_score":0.005649626,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01493465071521511,"score_gpt":0.2795408148129193,"score_spread":0.2646061640977042,"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."}}