{"id":"W4382656787","doi":"10.3389/fnins.2023.1222751","title":"Brain age prediction using the graph neural network based on resting-state functional MRI in Alzheimer's disease","year":2023,"lang":"en","type":"article","venue":"Frontiers in Neuroscience","topic":"Functional Brain Connectivity Studies","field":"Neuroscience","cited_by":46,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"National Institute on Aging; Canadian Institutes of Health Research; H. Lundbeck A/S; Servier; National Institutes of Health; Northern California Institute for Research and Education; University of Electronic Science and Technology of China; National Natural Science Foundation of China; Eisai; Genentech; IXICO; F. Hoffmann-La Roche; University of Southern California; Pfizer; BioClinica; Biogen; U.S. Department of Defense; Eli Lilly and Company; Bristol-Myers Squibb; Meso Scale Diagnostics; Alzheimer's Disease Neuroimaging Initiative; Novartis Pharmaceuticals Corporation; Sichuan Province Science and Technology Support Program; Alzheimer's Association","keywords":"Parahippocampal gyrus; Resting state fMRI; Functional magnetic resonance imaging; Neuroimaging; Neuroscience; Brain activity and meditation; Alzheimer's disease; Medicine; Disease; Psychology; Temporal lobe; Internal medicine; Electroencephalography","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":[0.0004379741,0.0005462416,0.0003844046,0.0008284698,0.0001861821,0.0003227764,0.0003378539,0.000477918,0.0007115896],"category_scores_gemma":[0.001700277,0.0001671235,0.0004594073,0.0003292673,0.0001984576,0.0005111619,0.0002319147,0.0003330259,0.0001267567],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004829802,"about_ca_system_score_gemma":0.0003211676,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01168122,"about_ca_topic_score_gemma":0.01215753,"domain_scores_codex":[0.9999031,0.0000375263,0.000003905321,0.00003243709,0.00001176167,0.00001120532],"domain_scores_gemma":[0.9996711,0.0002033549,0.0000416293,0.00001640805,0.00004830033,0.00001928239],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0003038881,0.0001341167,0.02268415,0.00008956507,0.0002299293,0.0002219145,0.00006562746,0.8981991,0.002225274,0.001974175,0.001808845,0.07206334],"study_design_scores_gemma":[0.000004331448,0.00002574766,0.003677046,0.000006793851,0.00002602708,0.00003761621,0.000005729957,0.9934268,0.0001805724,0.002496282,0.0001073679,0.000005691393],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7013723,0.003503097,0.2892102,0.001054905,0.0001278362,0.00008714237,0.001039283,0.0006446131,0.002960668],"genre_scores_gemma":[0.9850882,0.0005179347,0.01328446,0.0000503558,0.0000358092,0.0000338971,0.0003907493,0.00001560283,0.0005830993],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01168122,"threshold_uncertainty_score":0.0232265,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06347955674198463,"score_gpt":0.2725615074261303,"score_spread":0.2090819506841456,"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."}}