{"id":"W4205196630","doi":"10.1186/s12880-021-00729-7","title":"Deep learning-based pancreas volume assessment in individuals with type 1 diabetes","year":2022,"lang":"en","type":"article","venue":"BMC Medical Imaging","topic":"Pancreatitis Pathology and Treatment","field":"Medicine","cited_by":11,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"National Center for Advancing Translational Sciences; National Institute of Diabetes and Digestive and Kidney Diseases; Juvenile Diabetes Research Foundation Canada; Juvenile Diabetes Research Foundation International","keywords":"Pancreas; Magnetic resonance imaging; Medicine; Diabetes mellitus; Volume (thermodynamics); Convolutional neural network; Type 2 diabetes; Artificial intelligence; Computer science; Radiology; Nuclear medicine; Internal medicine; Endocrinology","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"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":[0.001015737,0.0004466171,0.0003581916,0.0008363672,0.0001525624,0.0008218141,0.0003535227,0.0004313119,0.001003089],"category_scores_gemma":[0.002570015,0.0002179588,0.0003759734,0.0004430628,0.000204178,0.0003909727,0.0006102427,0.0005497417,0.0002471862],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004850555,"about_ca_system_score_gemma":0.0002434034,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003903245,"about_ca_topic_score_gemma":0.004441924,"domain_scores_codex":[0.9997423,0.00009766912,0.00001849769,0.00006954601,0.00004333942,0.00002859612],"domain_scores_gemma":[0.9991878,0.0003214145,0.0001969517,0.00009309118,0.0001457692,0.00005501245],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.002122195,0.0003451501,0.6630005,0.0001663232,0.000436472,0.0003255207,0.0002307503,0.0733841,0.01892378,0.000750755,0.003087232,0.2372272],"study_design_scores_gemma":[0.0000574409,0.000353721,0.3293685,0.00009396614,0.0001324479,0.0006038018,0.0001476062,0.650802,0.01403069,0.003003643,0.001358489,0.00004770495],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.969509,0.0006905563,0.02696678,0.0002243542,0.00002180726,0.00003111873,0.0007320652,0.000407382,0.001416923],"genre_scores_gemma":[0.9863471,0.000171703,0.01218308,0.00007458712,0.00001272901,0.00002018093,0.0006413512,0.00002232572,0.0005270545],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.003903245,"threshold_uncertainty_score":0.007761061,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01060027862792575,"score_gpt":0.2840459359476392,"score_spread":0.2734456573197134,"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."}}