{"id":"W4400578756","doi":"10.1093/ehjdh/ztae051","title":"Machine learning-based prediction of 1-year all-cause mortality in patients undergoing CRT implantation: validation of the SEMMELWEIS-CRT score in the European CRT Survey I dataset","year":2024,"lang":"en","type":"article","venue":"European Heart Journal - Digital Health","topic":"Cardiac pacing and defibrillation studies","field":"Medicine","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Nemzeti Kutatási Fejlesztési és Innovációs Hivatal; Nemzeti Kutatási, Fejlesztési és Innovaciós Alap; Ministry of Advanced Education; Magyar Tudományos Akadémia; European Commission","keywords":"Medicine; Cardiac resynchronization therapy; Receiver operating characteristic; Internal medicine; Cohort; Heart failure; Odds ratio; Area under the curve; Ejection fraction; Cardiology","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.005729174,0.0006716528,0.0007742654,0.001160322,0.0002023701,0.000728579,0.0007184302,0.0006106296,0.001097795],"category_scores_gemma":[0.01267883,0.0001261959,0.001121349,0.0006804065,0.000295978,0.0003971675,0.001059331,0.0007762275,0.0005065666],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003002031,"about_ca_system_score_gemma":0.0005851089,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002519441,"about_ca_topic_score_gemma":0.002963171,"domain_scores_codex":[0.9979811,0.001091619,0.0001878619,0.0003987,0.0002205073,0.0001203208],"domain_scores_gemma":[0.993862,0.003095184,0.0009181001,0.001034488,0.0007029811,0.0003873006],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.001211446,0.0002760601,0.9611927,0.0001073037,0.0008183271,0.00009278513,0.00006809093,0.01203274,0.0007221811,0.0002009784,0.006096624,0.01718079],"study_design_scores_gemma":[0.0003983945,0.0008365525,0.8861875,0.00008761235,0.0003092835,0.0004763485,0.000116921,0.1066037,0.001148251,0.0006460244,0.003131747,0.00005759694],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9812835,0.0002605107,0.003310968,0.0002359348,0.0000447973,0.00006649732,0.01382802,0.0001473603,0.0008223372],"genre_scores_gemma":[0.9609526,0.00008734647,0.003164944,0.0001328849,0.00004814162,0.00009263219,0.03526399,0.00002370132,0.0002337651],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.005729174,"threshold_uncertainty_score":0.03029913,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1207262393877813,"score_gpt":0.3622328724889506,"score_spread":0.2415066331011693,"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."}}