{"id":"W2592815600","doi":"10.1117/12.2254418","title":"Automatic classification of patients with idiopathic Parkinson's disease and progressive supranuclear palsy using diffusion MRI datasets","year":2017,"lang":"en","type":"article","venue":"Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"Ontario Brain Institute; University of Calgary","funders":"","keywords":"Progressive supranuclear palsy; Diffusion MRI; Support vector machine; Effective diffusion coefficient; Magnetic resonance imaging; Computer science; Parkinson's disease; Context (archaeology); Artificial intelligence; Pattern recognition (psychology); Medicine; Disease; Radiology; Pathology","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001124924,0.0006728477,0.0007283859,0.002396948,0.0002494641,0.0007873432,0.0005100656,0.0008156034,0.0004607106],"category_scores_gemma":[0.00287949,0.0001165523,0.0005586535,0.0007567439,0.0001953969,0.0003927619,0.0006134505,0.0004001878,0.0003409768],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003085269,"about_ca_system_score_gemma":0.0004324987,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002295012,"about_ca_topic_score_gemma":0.002600906,"domain_scores_codex":[0.9993458,0.0001362159,0.0001327868,0.0001924879,0.0001200833,0.00007252147],"domain_scores_gemma":[0.9989836,0.0003937266,0.0001587736,0.0001315551,0.0002489759,0.00008334068],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.002871476,0.0009286292,0.450899,0.0004764117,0.0007729438,0.003150905,0.000462177,0.02486167,0.04725854,0.000812605,0.008442362,0.4590633],"study_design_scores_gemma":[0.000186554,0.0006395209,0.4432003,0.000144499,0.00035363,0.004931713,0.0008467122,0.511967,0.03066596,0.002432983,0.004524767,0.0001062881],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9701591,0.0009659478,0.02363221,0.000227897,0.00007563348,0.0001297045,0.003386686,0.0006461841,0.0007766051],"genre_scores_gemma":[0.9762807,0.0001999161,0.01724876,0.00004001702,0.00003630321,0.00006144864,0.00588027,0.0000173309,0.0002352595],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.002396948,"threshold_uncertainty_score":0.005949199,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02458622822985564,"score_gpt":0.2867815629657302,"score_spread":0.2621953347358745,"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."}}