{"id":"W4206577272","doi":"10.1016/j.nicl.2022.102940","title":"Automatic segmentation of white matter hyperintensities: validation and comparison with state-of-the-art methods on both Multiple Sclerosis and elderly subjects","year":2022,"lang":"en","type":"article","venue":"NeuroImage Clinical","topic":"Multiple Sclerosis Research Studies","field":"Medicine","cited_by":51,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Janssen Research and Development; National Institute on Aging; National Institute of Biomedical Imaging and Bioengineering; Canadian Institutes of Health Research; University of California, San Francisco; Meso Scale Diagnostics; Johnson and Johnson; National Institutes of Health; Genentech; IXICO; H. Lundbeck A/S; Servier; Eisai; Northern California Institute for Research and Education; Pfizer; Biogen; BioClinica; F. Hoffmann-La Roche; University of Southern California; Novartis Pharmaceuticals Corporation; U.S. Department of Defense; Eli Lilly and Company; Bristol-Myers Squibb; GE Healthcare; Alzheimer's Disease Neuroimaging Initiative; Merck; Fujirebio Europe; Alzheimer's Association; Foundation for the National Institutes of Health","keywords":"Fluid-attenuated inversion recovery; Hyperintensity; Multiple sclerosis; Segmentation; Dementia; White matter; Neuroimaging; CADASIL; Medicine; Cognition; Magnetic resonance imaging; Artificial intelligence; Computer science; Radiology; Disease; Pathology","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":[0.004920997,0.001800329,0.001562198,0.003499437,0.000908398,0.002004748,0.001716099,0.002654255,0.001613192],"category_scores_gemma":[0.006936671,0.000464061,0.001820659,0.001557015,0.0009316133,0.0009281292,0.00160014,0.0008814256,0.001476768],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005161185,"about_ca_system_score_gemma":0.001210327,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.007210556,"about_ca_topic_score_gemma":0.007612294,"domain_scores_codex":[0.9974067,0.0006711525,0.000287343,0.0009299497,0.0005028184,0.0002020454],"domain_scores_gemma":[0.9971429,0.001027082,0.0002660554,0.0005203818,0.0008805176,0.0001631876],"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":[0.004576554,0.0008148313,0.03164244,0.002734551,0.002315377,0.001379342,0.001832431,0.1149183,0.1302572,0.001735949,0.01154719,0.6962458],"study_design_scores_gemma":[0.0004165167,0.001617636,0.0653567,0.0004538251,0.0009420991,0.003457222,0.0009485943,0.7949418,0.1107635,0.002930689,0.01791603,0.0002554035],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6373244,0.01165494,0.3296657,0.0005598906,0.0007153138,0.0010609,0.003880998,0.0112662,0.003871731],"genre_scores_gemma":[0.6575267,0.002862263,0.3229769,0.0004019726,0.0002862726,0.0005785603,0.01059096,0.001561447,0.003214943],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.007210556,"threshold_uncertainty_score":0.02602506,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1369123166118126,"score_gpt":0.4050454498491978,"score_spread":0.2681331332373852,"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."}}