{"id":"W4391486149","doi":"10.3233/jad-231020","title":"Disentangling Accelerated Cognitive Decline from the Normal Aging Process and Unraveling Its Genetic Components: A Neuroimaging-Based Deep Learning Approach","year":2024,"lang":"en","type":"article","venue":"Journal of Alzheimer s Disease","topic":"Neuroinflammation and Neurodegeneration Mechanisms","field":"Neuroscience","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"National Institutes of Health; Cancer Prevention and Research Institute of Texas; Genentech; U.S. National Library of Medicine; IXICO; H. Lundbeck A/S; National Cancer Institute; Servier; Eisai; National Institute of Environmental Health Sciences; Northern California Institute for Research and Education; Pfizer; Biogen; BioClinica; University of Southern California; University of Texas Health Science Center at Houston; Meso Scale Diagnostics; Eli Lilly and Company; U.S. Department of Defense; Alzheimer's Disease Neuroimaging Initiative; Novartis Pharmaceuticals Corporation; Bristol-Myers Squibb; National Institute on Aging; Alzheimer's Association; Canadian Institutes of Health Research; National Science Foundation","keywords":"Neuroimaging; Genome-wide association study; Cognitive decline; Cognition; Neuroscience; Psychology; Imaging genetics; Biology; Disease; Dementia; Medicine; Genetics; Single-nucleotide polymorphism; Pathology; Gene","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":[0.001184777,0.0008616816,0.0007502828,0.0007173739,0.0002780758,0.0005636759,0.001003237,0.0009753997,0.0006858874],"category_scores_gemma":[0.001872274,0.0003578629,0.0009161073,0.0004781217,0.0005475322,0.0006601961,0.0008121371,0.001550588,0.0001629456],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007789176,"about_ca_system_score_gemma":0.001035385,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.006518962,"about_ca_topic_score_gemma":0.008320629,"domain_scores_codex":[0.9997963,0.00006087601,0.00001087756,0.00006937714,0.00002354469,0.0000390233],"domain_scores_gemma":[0.9993778,0.0003604767,0.00007243351,0.00004942732,0.00009231905,0.00004741544],"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":[0.0003921592,0.0005710293,0.03108206,0.0001282208,0.0005223539,0.0005170158,0.0001654156,0.7710816,0.009880725,0.005812063,0.002989213,0.1768582],"study_design_scores_gemma":[0.000009627956,0.00003853946,0.001859696,0.000007087284,0.00002712717,0.0000318387,0.000008458812,0.9920684,0.0004781527,0.005278023,0.0001865751,0.000006562972],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.3130767,0.001741688,0.6796656,0.002381822,0.00007877719,0.00008410135,0.0006610905,0.0006310875,0.001679155],"genre_scores_gemma":[0.9358618,0.0004643815,0.06014554,0.0004224187,0.00007156085,0.0001163137,0.0008408164,0.00003754442,0.002039651],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.006518962,"threshold_uncertainty_score":0.01296204,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0545133759248998,"score_gpt":0.3018785830911335,"score_spread":0.2473652071662337,"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."}}