{"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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00103624,0.0002608638,0.0002063318,0.0005825592,0.000794079,0.0001293676,0.0005021533,0.00004154243,0.000002936468],"category_scores_gemma":[0.007587435,0.0002227427,0.0000935589,0.004830991,0.0007676908,0.0004013018,0.0001968916,0.0004965103,0.000005796969],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001158267,"about_ca_system_score_gemma":0.0001320163,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002657295,"about_ca_topic_score_gemma":0.00003227792,"domain_scores_codex":[0.9962128,0.0006309534,0.000340438,0.001148058,0.000907247,0.0007605079],"domain_scores_gemma":[0.9963676,0.002892438,0.0001247355,0.00046018,0.00002512747,0.0001299325],"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":[0.0001935523,0.00006589454,0.09684546,0.000004752963,9.916299e-7,0.0001986797,0.00006228028,0.8658623,0.00295865,0.00009948431,0.03344679,0.0002611563],"study_design_scores_gemma":[0.0003295765,0.00008404364,0.3330128,0.00003548336,0.000005786314,0.000003516412,0.00002456562,0.6629139,0.0001219695,0.001951021,0.001368135,0.000149273],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9185971,0.0001374781,0.01931953,0.0346917,0.02415536,0.001757558,0.0001464938,0.000714713,0.0004800642],"genre_scores_gemma":[0.9855926,0.00002578186,0.00019418,0.01374524,0.0001861732,0.00009839366,0.000004218531,0.00003234371,0.0001210859],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2361673,"threshold_uncertainty_score":0.9083416,"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."}}