{"id":"W4221129115","doi":"10.1002/hbm.25784","title":"Deep Bayesian networks for uncertainty estimation and adversarial resistance of white matter hyperintensity segmentation","year":2022,"lang":"en","type":"article","venue":"Human Brain Mapping","topic":"Adversarial Robustness in Machine Learning","field":"Computer Science","cited_by":51,"is_retracted":false,"has_abstract":true,"ca_institutions":"Baycrest Hospital; Toronto Rehabilitation Institute; Ontario Brain Institute; Université de Montréal; Heart and Stroke Foundation; York University; Montreal Heart Institute; Toronto Western Hospital; University Health Network; Ottawa Hospital; Thunder Bay Regional Research Institute; University of Ottawa; Sunnybrook Health Science Centre; Centre Intégré Universitaire de Santé et de Services Sociaux du Centre-Sud-de-l'Île-de-Montréal; Western University; University of Toronto","funders":"Faculty of Health Sciences, Queen's University; London Health Sciences Foundation; Government of Ontario; St. Michael's Hospital Foundation; University Health Network; Temerty Family Foundation; Health Sciences Centre Foundation; Ontario Brain Institute; University of Ottawa; Queen's University; Canadian Institutes of Health Research; Centre for Addiction and Mental Health Foundation; McMaster University","keywords":"Hyperintensity; Segmentation; Artificial intelligence; Adversarial system; White matter; Bayesian probability; Pattern recognition (psychology); Computer science; Psychology; Magnetic resonance imaging; Medicine; Radiology","routes":{"ca_aff":true,"ca_fund":true,"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":[0.0007552433,0.0001255296,0.0001880138,0.0001214891,0.001174086,0.0000563755,0.0003458128,0.00003533607,0.00005155119],"category_scores_gemma":[0.00008772101,0.0001505115,0.00005301249,0.0002237482,0.00005507964,0.0002992113,0.0005113614,0.0001931257,4.8487e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001131097,"about_ca_system_score_gemma":0.00001927541,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002195296,"about_ca_topic_score_gemma":0.00002908581,"domain_scores_codex":[0.998706,0.0001934398,0.0002927571,0.0003703287,0.0002195785,0.0002179324],"domain_scores_gemma":[0.9991316,0.0002176171,0.0002653016,0.0002795809,0.0000665406,0.0000393176],"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":[0.00004386419,0.00001537658,0.00615409,0.00006705165,0.00001847432,0.000002581431,0.004586461,0.9739003,0.001196419,0.01181722,0.0007638676,0.001434359],"study_design_scores_gemma":[0.0006536359,0.00003873792,0.02813875,0.00002102794,0.00000741337,0.000005124984,0.000510746,0.9653844,0.000005334566,0.004685675,0.0003927351,0.0001564508],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.02004874,0.00002144603,0.9775921,0.001411122,0.0002724249,0.0003557683,0.000002157641,0.00006508555,0.0002312173],"genre_scores_gemma":[0.8600742,2.920469e-7,0.1390002,0.0005266921,0.00007654286,0.00004956911,0.00002997774,0.00001225639,0.0002302499],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.8400254,"threshold_uncertainty_score":0.9030235,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0137712265731811,"score_gpt":0.2520364986494728,"score_spread":0.2382652720762916,"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."}}