{"id":"W3207523440","doi":"10.3390/diagnostics11101893","title":"Automated Segmentation of Median Nerve in Dynamic Sonography Using Deep Learning: Evaluation of Model Performance","year":2021,"lang":"en","type":"article","venue":"Diagnostics","topic":"Peripheral Nerve Disorders","field":"Medicine","cited_by":27,"is_retracted":false,"has_abstract":true,"ca_institutions":"Centre Hospitalier de l’Université de Montréal","funders":"Ministry of Science and Technology, Taiwan","keywords":"Segmentation; Median nerve; Artificial intelligence; Deep learning; Wrist; Medicine; Carpal tunnel syndrome; Computer science; Radiology; Anatomy","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003126938,0.0000887804,0.0002120811,0.0001688831,0.00002018215,0.0000037121,0.00003728685,0.00007191202,0.00003269567],"category_scores_gemma":[0.0008543049,0.00009707623,0.00005613231,0.0005118162,0.00005171933,0.00008418045,0.00001812612,0.0001128999,8.897449e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001001359,"about_ca_system_score_gemma":0.0002193124,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00004408065,"about_ca_topic_score_gemma":0.0001207309,"domain_scores_codex":[0.9988969,0.00009219449,0.0003295101,0.0001356894,0.0004117188,0.0001339937],"domain_scores_gemma":[0.9991013,0.00009555277,0.0001498666,0.0001316031,0.0004824629,0.00003915556],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00002665299,0.0002112398,0.3484997,0.0001996677,0.00003501371,0.000007508228,0.001150816,0.6031892,0.03496936,0.000007284757,0.000006411395,0.01169718],"study_design_scores_gemma":[0.001223592,0.00006856507,0.2080719,0.0001863714,0.00013526,0.000004258939,0.0006924663,0.7795648,0.009945923,0.00004517457,6.827503e-7,0.00006095734],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9976945,0.0007431319,0.001064824,0.00006134967,0.00005472496,0.0002318077,0.000005918119,0.00003144617,0.0001123323],"genre_scores_gemma":[0.9928246,0.0004461276,0.006421127,0.00003178952,0.000005833662,0.00001305813,0.0002375372,0.00001549393,0.000004418703],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1763756,"threshold_uncertainty_score":0.3958654,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03721722020507704,"score_gpt":0.3454066700992385,"score_spread":0.3081894498941614,"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."}}