{"id":"W4360839182","doi":"10.1016/j.nicl.2023.103385","title":"Alzheimer’s and vascular disease classification using regional texture biomarkers in FLAIR MRI","year":2023,"lang":"en","type":"article","venue":"NeuroImage Clinical","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":16,"is_retracted":false,"has_abstract":true,"ca_institutions":"Baycrest Hospital; Health Sciences Centre; Sunnybrook Health Science Centre; Toronto Metropolitan University; University of Toronto; Canada Research Chairs; St. Michael's Hospital","funders":"Alzheimer Society; Alzheimer's Society; Government of Ontario; Consortium canadien en neurodégénérescence associée au vieillissement; Natural Sciences and Engineering Research Council of Canada; Université de Sherbrooke","keywords":"Fluid-attenuated inversion recovery; White matter; Medicine; Biomarker; Vascular dementia; Dementia; Diffusion MRI; Hyperintensity; Disease; Pathology; Imaging biomarker; Magnetic resonance imaging; Radiology; Internal medicine; Oncology; Biology","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001755434,0.0005951639,0.0005888065,0.003623596,0.0002212665,0.001284208,0.0002650144,0.0005690986,0.0006358766],"category_scores_gemma":[0.003393703,0.0001483956,0.0006284832,0.0008579456,0.0003038227,0.0008092946,0.0004830279,0.0002983479,0.0002804151],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002609842,"about_ca_system_score_gemma":0.0002747749,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002230963,"about_ca_topic_score_gemma":0.002915729,"domain_scores_codex":[0.9994973,0.0001298076,0.00007273098,0.0001198859,0.00009765151,0.00008262708],"domain_scores_gemma":[0.9989566,0.0002782158,0.0003542189,0.0001109421,0.0002147799,0.00008517857],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.002718494,0.0002005696,0.7497286,0.0001937971,0.000642676,0.000443398,0.0004072707,0.004899023,0.04022682,0.0004952237,0.001071083,0.1989731],"study_design_scores_gemma":[0.0000774186,0.0007817033,0.9206305,0.00009180648,0.0002692161,0.001223754,0.0005514266,0.06391417,0.009519645,0.001809251,0.00106082,0.00007033129],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9820047,0.0009985982,0.01523718,0.00008460469,0.00002719638,0.00006512168,0.0003893735,0.0001374709,0.001055818],"genre_scores_gemma":[0.9902813,0.0001731014,0.00893366,0.00002166362,0.00002287933,0.00002870532,0.0003260132,0.00001030609,0.0002022836],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.003623596,"threshold_uncertainty_score":0.009283721,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.3948666672909603,"score_gpt":0.4882103607668675,"score_spread":0.09334369347590721,"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."}}