{"id":"W4409958085","doi":"10.3389/fdgth.2025.1548448","title":"A novel transformer-based approach for cardiovascular disease detection","year":2025,"lang":"en","type":"article","venue":"Frontiers in Digital Health","topic":"ECG Monitoring and Analysis","field":"Medicine","cited_by":8,"is_retracted":false,"has_abstract":true,"ca_institutions":"Artificial Intelligence in Medicine (Canada)","funders":"","keywords":"Atrial fibrillation; Normal Sinus Rhythm; Medicine; Heart failure; Sinus rhythm; Random forest; Electrocardiography; Heart disease; Cardiology; Recall; Internal medicine; Artificial intelligence; Computer science","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":[0.000662785,0.0007567017,0.0008237138,0.002184811,0.0003515814,0.0008052855,0.0009801451,0.0006953109,0.001962054],"category_scores_gemma":[0.001637202,0.0002253865,0.0009062807,0.001292187,0.0002678128,0.001009035,0.0006719627,0.0005946125,0.001210392],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003418441,"about_ca_system_score_gemma":0.0006655891,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002443871,"about_ca_topic_score_gemma":0.002581816,"domain_scores_codex":[0.9994189,0.00007416114,0.00005271893,0.0001745549,0.0002060928,0.00007370987],"domain_scores_gemma":[0.9995629,0.000150203,0.0000394386,0.00004159214,0.0001776895,0.00002821645],"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":[0.000392448,0.000202417,0.005470528,0.0001542573,0.0001194778,0.0003246156,0.00007962577,0.02372889,0.04336279,0.003464197,0.004468278,0.9182326],"study_design_scores_gemma":[0.00004654862,0.0002600427,0.004432125,0.0000197038,0.0001075937,0.001578994,0.00006314495,0.9610789,0.02286221,0.00512405,0.00439139,0.00003530469],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.01798819,0.0003489731,0.9786487,0.00008142675,0.00006566325,0.00008888595,0.0001768325,0.001339435,0.001261911],"genre_scores_gemma":[0.4704833,0.0005939976,0.5242799,0.0002169325,0.000108227,0.0001246435,0.001064627,0.00008909263,0.003039312],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.002443871,"threshold_uncertainty_score":0.006563783,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01592701079432039,"score_gpt":0.2711139484159483,"score_spread":0.2551869376216279,"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."}}