{"id":"W4415792254","doi":"10.1161/circ.152.suppl_3.4370574","title":"Abstract 4370574: Artificial Intelligence-Enabled Electrocardiography Demonstrates Strong Diagnostic Performance for Diastolic Dysfunction, Heart Failure with Preserved Ejection Fraction, and Left Atrial Enlargement: A Meta-Analysis","year":2025,"lang":"en","type":"article","venue":"Circulation","topic":"ECG Monitoring and Analysis","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"","keywords":"Receiver operating characteristic; Heart failure; Ejection fraction; Diastole; Electrocardiography; Heart failure with preserved ejection fraction; Meta-analysis; Diagnostic accuracy","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":[0.02174917,0.002379329,0.01249405,0.004800003,0.0005456567,0.004289753,0.001967903,0.002326672,0.004308109],"category_scores_gemma":[0.05331638,0.0009880089,0.0378379,0.005276081,0.0009219934,0.001877205,0.001349455,0.002130308,0.0005027695],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00163925,"about_ca_system_score_gemma":0.001941085,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004386729,"about_ca_topic_score_gemma":0.006828231,"domain_scores_codex":[0.9850807,0.00827097,0.003681711,0.001381749,0.001273007,0.0003120406],"domain_scores_gemma":[0.9511259,0.04054435,0.004930074,0.001362546,0.001726549,0.0003105071],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"meta_analysis","study_design_gemma":"meta_analysis","study_design_scores_codex":[0.002699802,0.00002477554,0.008510252,0.1450299,0.833541,0.0001353537,0.00005892274,0.0006092481,0.000313394,0.0001124816,0.0008843222,0.008080581],"study_design_scores_gemma":[0.0007414287,0.0001822565,0.005602298,0.009671063,0.9821114,0.0000671145,0.00002097923,0.0003381677,0.0001134163,0.0002684109,0.0008642323,0.0000192072],"study_design_candidate":"meta_analysis","study_design_consensus":"meta_analysis","genre_codex":"review","genre_gemma":"review","genre_scores_codex":[0.02148337,0.970641,0.002518843,0.0009082638,0.0004516622,0.000631761,0.00231397,0.0001167413,0.000934513],"genre_scores_gemma":[0.644513,0.3377577,0.007558301,0.002714914,0.001007378,0.002076688,0.003206314,0.0001237916,0.001041913],"genre_candidate":"review","genre_consensus":"review","teacher_disagreement_score":0.02174917,"threshold_uncertainty_score":0.1150219,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03232386969899084,"score_gpt":0.2824774965595374,"score_spread":0.2501536268605465,"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."}}