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To improve outcomes and enable preventative strategies, the electrocardiogram (ECG) in conjunction with deep learning was explored as a potential screening tool.<\/jats:p>\n               <\/jats:sec>\n               <jats:sec>\n                  <jats:title>Methods and results<\/jats:title>\n                  <jats:p>A publicly available data set containing 10\u2005s of 12-lead ECGs from individuals who did and did not have an SCA, information about time from ECG to arrest, and age and sex was utilized for analysis to individually predict SCA or not using deep convolution neural network models. The base model that included age and sex, ECGs within 1 day prior to arrest, and data sampled from windows of 720\u2005ms around the R-waves from 221 individuals with SCA and 1046 controls had an area under the receiver operating characteristic curve of 0.77. With sensitivity set at 95%, base model specificity was 31%, which is not clinically applicable. Gradient-weighted class activation mapping showed that the model mostly relied on the QRS complex to make predictions. However, models with ECGs recorded between 1 day to 1 month and 1 month to 1 year prior to arrest demonstrated predictive capabilities.<\/jats:p>\n               <\/jats:sec>\n               <jats:sec>\n                  <jats:title>Conclusion<\/jats:title>\n                  <jats:p>Deep learning models processing ECG data are a promising means of screening for SCA, and this method explains differences in SCAs due to age and sex. Model performance improved when ECGs were nearer in time to SCAs, although ECG data up to a year prior had predictive value. Sudden cardiac arrest prediction was more dependent upon QRS complex data compared to other ECG segments.<\/jats:p>\n               <\/jats:sec>","DOI":"10.1093\/ehjdh\/ztae088","type":"journal-article","created":{"date-parts":[[2025,2,25]],"date-time":"2025-02-25T01:37:06Z","timestamp":1740447426000},"page":"170-179","source":"Crossref","is-referenced-by-count":14,"title":["Sudden cardiac arrest prediction via deep learning electrocardiogram analysis"],"prefix":"10.1093","volume":"6","author":[{"given":"Matt T","family":"Oberdier","sequence":"first","affiliation":[{"name":"Department of Medicine, Division of Cardiology, Johns Hopkins University , Baltimore, MD 21205 ,","place":["USA"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-3971-9533","authenticated-orcid":false,"given":"Luca","family":"Neri","sequence":"additional","affiliation":[{"name":"Department of Medicine, Division of Cardiology, Johns Hopkins University , Baltimore, MD 21205 ,","place":["USA"]},{"name":"Department of Medical and Surgical Sciences, University of Bologna , 40138 Bologna ,","place":["Italy"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Alessandro","family":"Orro","sequence":"additional","affiliation":[{"name":"Institute of Biomedical Technologies, Department of Biomedical Sciences, National Research Council (ITB-CNR) , 20054 Segrate ,","place":["Italy"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Richard T","family":"Carrick","sequence":"additional","affiliation":[{"name":"Department of Medicine, Division of Cardiology, Johns Hopkins University , Baltimore, MD 21205 ,","place":["USA"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Marco S","family":"Nobile","sequence":"additional","affiliation":[{"name":"Department of Environmental Sciences, Informatics and Statistics, Ca\u2019 Foscari University of Venice , 30172 Mestre (Venice) ,","place":["Italy"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Sujai","family":"Jaipalli","sequence":"additional","affiliation":[{"name":"Department of Biomedical Engineering, Johns Hopkins University , Baltimore, MD 21205 ,","place":["USA"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Mariam","family":"Khan","sequence":"additional","affiliation":[{"name":"Department of Medicine, Division of Cardiology, Johns Hopkins University , Baltimore, MD 21205 ,","place":["USA"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Stefano","family":"Diciotti","sequence":"additional","affiliation":[{"name":"Department of Electrical, Electronic, and Information Engineering \u2018Guglielmo Marconi\u2019, University of Bologna , 47521 Cesena ,","place":["Italy"]},{"name":"Alma Mater Research Institute for Human-Centred Artificial Intelligence, University of Bologna , 40121 Bologna ,","place":["Italy"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-8039-8781","authenticated-orcid":false,"given":"Claudio","family":"Borghi","sequence":"additional","affiliation":[{"name":"Department of Medical and Surgical Sciences, University of Bologna , 40138 Bologna ,","place":["Italy"]},{"name":"Cardiovascular Medicine Unit, IRCCS Azienda Ospedaliero-Universitaria di Bologna , 40138 Bologna ,","place":["Italy"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Henry R","family":"Halperin","sequence":"additional","affiliation":[{"name":"Department of Medicine, Division of Cardiology, Johns Hopkins University , Baltimore, MD 21205 ,","place":["USA"]},{"name":"Department of Biomedical Engineering, Johns Hopkins University , Baltimore, MD 21205 ,","place":["USA"]},{"name":"Department of Radiology, Johns Hopkins University , Baltimore, MD 21205 ,","place":["USA"]}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"286","published-online":{"date-parts":[[2025,2,25]]},"reference":[{"key":"2025031807381467200_ztae088-B1","doi-asserted-by":"crossref","first-page":"e56","DOI":"10.1161\/CIR.0000000000000659","article-title":"Heart disease and stroke statistics\u20142019 update: a report from the American Heart Association","volume":"139","author":"Benjamin","year":"2019","journal-title":"Circulation"},{"key":"2025031807381467200_ztae088-B2","doi-asserted-by":"crossref","first-page":"417","DOI":"10.1161\/CIR.0b013e31829d8654","article-title":"Cardiopulmonary resuscitation quality: improving cardiac resuscitation outcomes both inside and outside the hospital: a consensus statement from the American Heart Association","volume":"128","author":"Meaney","year":"2013","journal-title":"Circulation"},{"key":"2025031807381467200_ztae088-B3","doi-asserted-by":"crossref","first-page":"606","DOI":"10.1161\/01.CIR.51.4.606","article-title":"Precursors of sudden coronary death. 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