{"id":"W4319765238","doi":"10.3390/s23041914","title":"A Convolutional Neural Network and Graph Convolutional Network Based Framework for AD Classification","year":2023,"lang":"en","type":"article","venue":"Sensors","topic":"Dementia and Cognitive Impairment Research","field":"Medicine","cited_by":31,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"National Institute of Biomedical Imaging and Bioengineering; Canadian Institutes of Health Research; National Institutes of Health; Servier; H. Lundbeck A/S; Natural Science Foundation of Beijing Municipality; Eisai; National Natural Science Foundation of China; BioClinica; Northern California Institute for Research and Education; F. Hoffmann-La Roche; University of Southern California; Biogen; Eli Lilly and Company; Bristol-Myers Squibb; National Institute on Aging; Alzheimer's Association; Foundation for the National Institutes of Health; U.S. Department of Defense","keywords":"Convolutional neural network; Computer science; Graph; Population; Artificial intelligence; Pattern recognition (psychology); Feature extraction; Machine learning; Theoretical computer science; Medicine","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":[0.0004953599,0.0001438813,0.000200089,0.0001168733,0.0002856397,0.00003067235,0.00005295334,0.0001222867,0.0001654106],"category_scores_gemma":[0.0002469074,0.0001347368,0.0001196094,0.0006052036,0.0002166328,0.00004085264,0.0000308905,0.0002185886,0.00006489208],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003985696,"about_ca_system_score_gemma":0.0001213121,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000003786487,"about_ca_topic_score_gemma":0.000003955794,"domain_scores_codex":[0.9983833,0.00008832882,0.000222213,0.000339784,0.0003948782,0.0005714851],"domain_scores_gemma":[0.9987072,0.0006474325,0.00006300218,0.000151652,0.0002375406,0.0001931948],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.002948676,0.0002906363,0.8075475,0.0003436059,0.0004401144,0.00006836027,0.0001156038,0.00847525,0.0009253896,0.06897002,0.100285,0.009589908],"study_design_scores_gemma":[0.001519802,0.0002945274,0.7804216,0.0001001497,0.00007828448,0.00001272532,0.000114014,0.1942526,0.00002157629,0.01429333,0.008758694,0.0001327404],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9745261,0.0004168523,0.01336554,0.008932768,0.0004868689,0.001329816,0.00006702387,0.0002385204,0.0006365297],"genre_scores_gemma":[0.9910394,0.00007237715,0.005188297,0.00104993,0.0006291542,0.000179349,0.0005144995,0.00002627998,0.001300702],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1857774,"threshold_uncertainty_score":0.5494408,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0478953458124065,"score_gpt":0.3370199579418627,"score_spread":0.2891246121294562,"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."}}