{"id":"W4413366722","doi":"10.1016/j.bspc.2025.108390","title":"Dual-Transformer Cross-Attention Framework for Alzheimer’s disease detection via dPTE-Guided EEG channel selection and multi-modal integration","year":2025,"lang":"en","type":"article","venue":"Biomedical Signal Processing and Control","topic":"EEG and Brain-Computer Interfaces","field":"Neuroscience","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Calgary; University of Manitoba; University of Winnipeg","funders":"Natural Sciences and Engineering Research Council of Canada; Manitoba Medical Service Foundation","keywords":"Computer science; Electroencephalography; Selection (genetic algorithm); Transformer; Dual (grammatical number); Modal; Speech recognition; Pattern recognition (psychology); Artificial intelligence; Neuroscience; Psychology; Voltage; Electrical engineering; Engineering","routes":{"ca_aff":true,"ca_fund":true,"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":[0.0007988806,0.000908195,0.000673026,0.0008288907,0.000310219,0.0006609178,0.001129498,0.0008142898,0.001747776],"category_scores_gemma":[0.001288824,0.0003456858,0.0008997619,0.0005205252,0.0003816206,0.0008139139,0.001021944,0.001114657,0.0004640458],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005961123,"about_ca_system_score_gemma":0.0009505769,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.008786663,"about_ca_topic_score_gemma":0.01247256,"domain_scores_codex":[0.9997677,0.00004792355,0.00001123018,0.00007963653,0.00004584294,0.00004767238],"domain_scores_gemma":[0.9997302,0.0001083201,0.00002277394,0.00002026783,0.00009199998,0.00002641433],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0006019056,0.000392203,0.005532543,0.000148618,0.0002805835,0.0003695844,0.0001766057,0.3598406,0.03433518,0.007480521,0.007507232,0.5833344],"study_design_scores_gemma":[0.00000743339,0.00003573274,0.0006439929,0.000005856275,0.00002959528,0.00005618998,0.000009495997,0.9929997,0.002673846,0.00295947,0.0005697525,0.000009055942],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.04971683,0.001284623,0.9440069,0.0005252933,0.0001017929,0.00006330265,0.0002553845,0.001498161,0.002547672],"genre_scores_gemma":[0.8415384,0.000740297,0.1484679,0.0006030954,0.0001865828,0.0001434246,0.0007651369,0.0001504555,0.007404647],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.008786663,"threshold_uncertainty_score":0.01747108,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02737270663652254,"score_gpt":0.3238745029176055,"score_spread":0.296501796281083,"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."}}