{"id":"W4210807272","doi":"10.1002/alz.053259","title":"Discovering genetic biomarkers for Alzheimer’s disease using 2D‐CNN and GWAS","year":2021,"lang":"en","type":"article","venue":"Alzheimer s & Dementia","topic":"Bioinformatics and Genomic Networks","field":"Biochemistry, Genetics and Molecular Biology","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Surrey Memorial Hospital","funders":"","keywords":"Discriminative model; Genome-wide association study; Artificial intelligence; Computer science; Convolutional neural network; Pattern recognition (psychology); Classifier (UML); Neuroimaging; Machine learning; Single-nucleotide polymorphism; Biology; Neuroscience; Genotype; Genetics; Gene","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000858512,0.0007148754,0.0005571739,0.001289525,0.0002542764,0.0005876917,0.0006018322,0.0005875477,0.001226783],"category_scores_gemma":[0.001252011,0.0002905999,0.0009247948,0.000934147,0.0001889871,0.0003937737,0.000456476,0.0004831462,0.0002666965],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005558949,"about_ca_system_score_gemma":0.0004621835,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01024436,"about_ca_topic_score_gemma":0.01127753,"domain_scores_codex":[0.9997516,0.00005128739,0.0000148538,0.00009676209,0.00004114303,0.00004428626],"domain_scores_gemma":[0.9997029,0.0001056912,0.00004616589,0.00004668487,0.00007453885,0.00002413883],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0007014411,0.0002839066,0.4231114,0.0002300199,0.001116363,0.00101486,0.0001222058,0.1993574,0.02961431,0.003500347,0.006288491,0.3346592],"study_design_scores_gemma":[0.00002025068,0.00007042499,0.05808638,0.00002323757,0.000152632,0.0003034914,0.0000411113,0.9315342,0.005549296,0.002881323,0.001313063,0.00002466844],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6158152,0.002191681,0.3712567,0.001008838,0.0001515625,0.0001335688,0.004746623,0.001539047,0.003156632],"genre_scores_gemma":[0.9334559,0.0004281607,0.06190439,0.000151822,0.00004798108,0.0001011426,0.002571849,0.00003045809,0.001308326],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01024436,"threshold_uncertainty_score":0.02036947,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02267792593118598,"score_gpt":0.2633191187540707,"score_spread":0.2406411928228847,"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."}}