{"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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.000329481,0.0002488385,0.0003093007,0.0002715623,0.0003460849,0.0001320847,0.0001104262,0.00003751666,0.0001655807],"category_scores_gemma":[0.0005538746,0.0002456678,0.0000742887,0.000206034,0.00005088152,0.0002795129,0.0002595811,0.0002900802,0.000009202376],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002988047,"about_ca_system_score_gemma":0.00005399116,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0006194297,"about_ca_topic_score_gemma":0.00004509105,"domain_scores_codex":[0.9976911,0.0003207006,0.0004282196,0.0006057951,0.0006483402,0.0003058291],"domain_scores_gemma":[0.9989399,0.0001546817,0.0001873239,0.0002187731,0.0001382293,0.0003610962],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00006186445,0.00004686547,0.5634561,0.0001481034,0.0001779658,0.00003628278,0.0007912175,0.0002332447,0.4337395,0.00007600013,0.0001478803,0.001085071],"study_design_scores_gemma":[0.001401817,0.0003657485,0.9198423,0.000387437,0.0003423714,0.00000239894,0.0006396854,0.008744671,0.06776959,0.00007414685,0.0003034776,0.0001263315],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9861087,0.0006722119,0.01094936,0.001243646,0.00006416252,0.0007577954,0.0001266676,0.00005639036,0.00002105864],"genre_scores_gemma":[0.9953781,0.00003839314,0.001470702,0.001166796,0.0002559318,0.0000199428,0.001608133,0.00003870121,0.00002334866],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3659699,"threshold_uncertainty_score":0.9999996,"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."}}