{"id":"W3181173354","doi":"","title":"心筋血流SPECTの虚血判定におけるANN(人工ニューラルネットワーク)解析による読影支援の可能性","year":2021,"lang":"ja","type":"article","venue":"Pharma Medica","topic":"Cardiac Imaging and Diagnostics","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Artificial intelligence; Computer science","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":[0.001580382,0.0004411276,0.0003784486,0.0005768979,0.0005368576,0.001429065,0.0003149645,0.0008053692,0.004746914],"category_scores_gemma":[0.001795987,0.0002955787,0.0002858516,0.0003958207,0.001167017,0.001337683,0.0003874756,0.0007718251,0.001062261],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008530469,"about_ca_system_score_gemma":0.0007860209,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002827354,"about_ca_topic_score_gemma":0.003405419,"domain_scores_codex":[0.9995659,0.0001192751,0.00003221934,0.00009848359,0.0001428872,0.00004128564],"domain_scores_gemma":[0.9990753,0.0003485025,0.0001377639,0.00006231533,0.0002892392,0.00008681705],"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":[0.001491463,0.0003993427,0.09835403,0.001414087,0.0005419455,0.005908675,0.002159615,0.004035285,0.3467632,0.03908594,0.00968233,0.4901642],"study_design_scores_gemma":[0.0002811158,0.002041046,0.291652,0.0005442252,0.001163727,0.02047977,0.003156003,0.02653378,0.4913609,0.05870796,0.1037446,0.0003349326],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6471476,0.01980602,0.1235983,0.006020804,0.0007780207,0.0003711008,0.0008883423,0.0008291359,0.2005607],"genre_scores_gemma":[0.9318554,0.004019316,0.03092454,0.0009390317,0.0004653095,0.0001632876,0.0002627219,0.0001124291,0.03125797],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.004746914,"threshold_uncertainty_score":0.01587999,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02245401079338172,"score_gpt":0.3249207252323157,"score_spread":0.302466714438934,"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."}}