{"id":"W3203736792","doi":"10.2196/30066","title":"Deep Learning Techniques for Fatty Liver Using Multi-View Ultrasound Images Scanned by Different Scanners: Development and Validation Study","year":2021,"lang":"en","type":"article","venue":"JMIR Medical Informatics","topic":"Liver Disease Diagnosis and Treatment","field":"Medicine","cited_by":32,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Ministry of Science and ICT, South Korea; National Research Foundation of Korea; Ministry of Environment; National Research Foundation","keywords":"Fatty liver; Magnetic resonance imaging; Ultrasound; Artificial intelligence; Overfitting; Medicine; Liver disease; Radiology; Computer science; Artificial neural network; Pathology; Disease; Internal medicine","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":[0.002111024,0.001025711,0.0005270542,0.0011168,0.0001964134,0.0003616037,0.0008944405,0.0008789364,0.0009312002],"category_scores_gemma":[0.003518209,0.0003628416,0.0008200981,0.000584184,0.0002618188,0.00059921,0.0008683834,0.0007469574,0.0004074939],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005736784,"about_ca_system_score_gemma":0.0005691983,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.006110163,"about_ca_topic_score_gemma":0.004945585,"domain_scores_codex":[0.9992923,0.0001699851,0.0000603004,0.000142354,0.0002436107,0.0000915217],"domain_scores_gemma":[0.9982823,0.0006002158,0.00015367,0.0002130481,0.0006710179,0.00007969602],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0009953068,0.001550707,0.05299817,0.0004185002,0.0006872534,0.0004969467,0.0001838098,0.2238691,0.05189553,0.0007411437,0.003175935,0.6629876],"study_design_scores_gemma":[0.00006029308,0.0007561601,0.01532317,0.00007841093,0.000139926,0.0003206226,0.00007350818,0.9588849,0.02292828,0.0002787509,0.001131299,0.00002456521],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8814718,0.003057186,0.110845,0.0002410493,0.00009424236,0.000265833,0.0005899582,0.001184777,0.002250158],"genre_scores_gemma":[0.9236467,0.0008206833,0.07161079,0.0001053482,0.00002036059,0.0001385667,0.001563836,0.00006849756,0.002025122],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.006110163,"threshold_uncertainty_score":0.01214921,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03133769379409989,"score_gpt":0.3289429064923638,"score_spread":0.2976052126982639,"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."}}