{"id":"W3040008283","doi":"10.1002/hbm.25115","title":"Using machine learning to quantify structural <scp>MRI</scp> neurodegeneration patterns of Alzheimer's disease into dementia score: Independent validation on 8,834 images from ADNI, AIBL, OASIS, and MIRIAD databases","year":2020,"lang":"en","type":"article","venue":"Human Brain Mapping","topic":"Dementia and Cognitive Impairment Research","field":"Medicine","cited_by":92,"is_retracted":false,"has_abstract":true,"ca_institutions":"Simon Fraser University","funders":"National Center for Research Resources; National Institute of Mental Health; Natural Sciences and Engineering Research Council of Canada; Engineering and Physical Sciences Research Council; Compute Canada; Canadian Institutes of Health Research; National Institutes of Health; National Institute on Aging; Alzheimer's Association; Alzheimer Society Research Program; Alzheimer's Society; Wellcome Trust; National Institute of Biomedical Imaging and Bioengineering; Michael Smith Health Research BC; Medical Research Council","keywords":"Neuroimaging; Dementia; Neurodegeneration; Magnetic resonance imaging; Alzheimer's Disease Neuroimaging Initiative; Discriminative model; Biomarker; Atrophy; Artificial intelligence; Neuroscience; Psychology; Disease; Medicine; Internal medicine; Computer science; Biology; 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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00557077,0.001942309,0.001280205,0.002685291,0.000486477,0.001125845,0.001232654,0.001562082,0.0006796297],"category_scores_gemma":[0.005516437,0.0002788257,0.001260552,0.001166341,0.0005624413,0.0007594741,0.001232406,0.001066038,0.0008623428],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006237063,"about_ca_system_score_gemma":0.0007799831,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.009296762,"about_ca_topic_score_gemma":0.00806874,"domain_scores_codex":[0.9980186,0.0005615955,0.0002113547,0.0005250693,0.0004653265,0.0002180804],"domain_scores_gemma":[0.9976436,0.0007382956,0.0002063683,0.000350047,0.0008279384,0.0002336814],"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":[0.004852865,0.003451362,0.329634,0.000846366,0.004162255,0.0009112571,0.0003983116,0.1287028,0.02683418,0.0003835178,0.02357506,0.4762479],"study_design_scores_gemma":[0.0002447908,0.001585998,0.1572911,0.0001195963,0.0004747322,0.0008649306,0.0003009739,0.8178334,0.01781794,0.0005794895,0.002809691,0.00007736417],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9800607,0.001697365,0.01008548,0.0002167837,0.0001653325,0.0002778601,0.004651362,0.001528732,0.00131636],"genre_scores_gemma":[0.9698711,0.0003689497,0.01229054,0.0001022615,0.00005354624,0.0001308738,0.01620096,0.00005220488,0.0009295487],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.009296762,"threshold_uncertainty_score":0.02946138,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1034402749028413,"score_gpt":0.3538833464365511,"score_spread":0.2504430715337098,"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."}}