NEWS AND VIEWS24 June 2026A machine-learning model trained on thousands of electrocardiogram recordings identifies a previously unrecognized group of at-risk people.ByChangxin Lai ORCID: http://orcid.org/0000-0002-3585-59790Changxin LaiChangxin Lai is at Johns Hopkins University, Baltimore, Maryland, 21218, USA, and EnChannel Medical Ltd, Irvine, California, USA.View author publicationsSearch author on: PubMed Google ScholarSudden cardiac death claims hundreds of thousands of lives annually, often striking without warning in people who had seemed reasonably healthy. Implantable defibrillators can terminate the lethal heart rhythms that are responsible, but deciding who should receive a defibrillator depends on accurate risk prediction. The current clinical tools for this miss most people who eventually succumb and flag many who never benefit. Writing in Nature, Obermeyer et al.1 describe a deep-learning model trained on population-scale electrocardiogram (ECG) data and death records. With this model, the authors identify a new high-risk group and discover features of the ECG trace that could be used to predict risk of sudden death.Access optionsAccess Nature and 54 other Nature Portfolio journalsGet Nature+, our best-value online-access subscription27,99 € / 30 dayscancel any timeLearn moreSubscribe to this journalReceive 52 print issues and online access199,00 € per yearonly 3,83 € per issueLearn moreRent or buy this articlePrices vary by article typefrom$1.95to$39.95Learn morePrices may be subject to local taxes which are calculated during checkoutdoi: https://doi.org/10.1038/d41586-026-01806-zReferencesObermeyer, Z., Schubert, A., Ross, J., Mullainathan, S. & Lingman, M. Nature https://doi.org/10.1038/s41586-026-10674-6 (2026).Article Google Scholar Stecker, E. C. et al. J. Am. Coll. Cardiol. 47, 1161–1166 (2006).Article PubMed Google Scholar Merchant, F. M., Quest, T., Leon, A. R. & El-Chami, M. F. J. Am. Coll. Cardiol. 67, 435–444 (2016).Article PubMed Google Scholar Trayanova, N. A. & Topol, E. J. Lancet 399, 1933 (2022).Article PubMed Google Scholar Niederer, S. A., Lumens, J. & Trayanova, N. A. Nature Rev. Cardiol. 16, 100–111 (2019).Article PubMed Google Scholar Download referencesCompeting InterestsThe author declares no competing interests. Read the paper: An ECG biomarker for sudden cardiac death discovered with deep learning An open AI model could help medical experts to interpret chest X-rays Machine learning improves health-care access in Sierra LeoneSee all News & ViewsSubjectsHealth careMachine learningCardiovascular biologyMedical researchLatest on:Health careMachine learningCardiovascular biologyJobs Associate or Senior Editor, Nature Reviews MaterialsTitle: Associate or Senior Editor, Nature Reviews Materials Location: Berlin, Heidelberg, Madrid, Milan and Pune – hybrid working model Closing da...Berlin (DE), Heidelberg, Madrid, Milan and PuneSpringer Nature LtdInterim Associate/Senior Editor - BMC Musculoskeletal DisordersJob Description Job Title: Interim Associate/Senior Editor - BMC Musculoskeletal Disorders Fixed-Term contract (Maternity Leave Cover) Locations: ...London (Central), London (Greater) (GB)Springer Nature LtdTalent Recruitment Announcement of the College of Informatics, Huazhong Agricultural UniversityJoin Huazhong Agricultural UniversityNo.1 Shizishan Street, Hongshan District, Wuhan, Hubei Province, ChinaHuazhong Agricultural University (HZAU)