{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,9,17]],"date-time":"2026-09-17T18:33:26Z","timestamp":1789670006378,"version":"4.0.1"},"reference-count":115,"publisher":"The Royal Society","issue":"194","license":[{"start":{"date-parts":[[2025,8,14]],"date-time":"2025-08-14T00:00:00Z","timestamp":1755129600000},"content-version":"vor","delay-in-days":1078,"URL":"http:\/\/creativecommons.org\/licenses\/by\/4.0\/"},{"start":{"date-parts":[[2025,8,14]],"date-time":"2025-08-14T00:00:00Z","timestamp":1755129600000},"content-version":"vor","delay-in-days":1078,"URL":"http:\/\/creativecommons.org\/licenses\/by\/4.0\/"},{"start":{"date-parts":[[2025,8,14]],"date-time":"2025-08-14T00:00:00Z","timestamp":1755129600000},"content-version":"vor","delay-in-days":1078,"URL":"http:\/\/creativecommons.org\/licenses\/by\/4.0\/"},{"start":{"date-parts":[[2022,9,1]],"date-time":"2022-09-01T00:00:00Z","timestamp":1661990400000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/royalsociety.org\/journals\/ethics-policies\/data-sharing-mining\/"}],"funder":[{"DOI":"10.13039\/501100003246","name":"Nederlandse Organisatie voor Wetenschappelijk Onderzoek","doi-asserted-by":"crossref","award":["17983"],"award-info":[{"award-number":["17983"]}],"id":[{"id":"10.13039\/501100003246","id-type":"DOI","asserted-by":"crossref"}]},{"name":"Eindhoven MedTech Innovation Center","award":["TKI HTSM\/20.0022"],"award-info":[{"award-number":["TKI HTSM\/20.0022"]}]},{"DOI":"10.13039\/501100003246","name":"Nederlandse Organisatie voor Wetenschappelijk Onderzoek","doi-asserted-by":"crossref","award":["17983"],"award-info":[{"award-number":["17983"]}],"id":[{"id":"10.13039\/501100003246","id-type":"DOI","asserted-by":"crossref"}]},{"name":"Eindhoven MedTech Innovation Center","award":["TKI HTSM\/20.0022"],"award-info":[{"award-number":["TKI HTSM\/20.0022"]}]}],"content-domain":{"domain":["royalsocietypublishing.org"],"crossmark-restriction":true},"short-container-title":[],"published-print":{"date-parts":[[2022,9,1]]},"abstract":"<jats:title>Abstract<\/jats:title>\n                  <jats:p>Survivors of myocardial infarction are at risk of life-threatening ventricular tachycardias (VTs) later in their lives. Current guidelines for implantable cardioverter defibrillators (ICDs) implantation to prevent VT-related sudden cardiac death is solely based on symptoms and left ventricular ejection fraction. Catheter ablation of scar-related VTs is performed following ICD therapy, reducing VTs, painful shocks, anxiety, depression and worsening heart failure. We postulate that better prediction of the occurrence and circuit of VT, will improve identification of patients at risk for VT and boost preventive ablation, reducing mortality and morbidity. For this purpose, multiple time-evolving aspects of the underlying pathophysiology, including the anatomical substrate, triggers and modulators, should be part of VT prediction models. We envision digital twins as a solution combining clinical expertise with three prediction approaches: evidence-based medicine (clinical practice), data-driven models (data science) and mechanistic models (biomedical engineering). This paper aims to create a mutual understanding between experts in the different fields by providing a comprehensive description of the clinical problem and the three approaches in an understandable manner, leveraging future collaborations and technological innovations for clinical decision support. Moreover, it defines open challenges and gains for digital twin solutions and discusses the potential of hybrid modelling.<\/jats:p>","DOI":"10.1098\/rsif.2022.0317","type":"journal-article","created":{"date-parts":[[2022,9,21]],"date-time":"2022-09-21T03:06:14Z","timestamp":1663729574000},"update-policy":"https:\/\/doi.org\/10.1098\/crossmark-policy","source":"Crossref","is-referenced-by-count":41,"title":["From evidence-based medicine to digital twin technology for predicting ventricular tachycardia in ischaemic cardiomyopathy"],"prefix":"10.1098","volume":"19","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-7023-9234","authenticated-orcid":false,"given":"Anouk G. W.","family":"de Lepper","sequence":"first","affiliation":[{"name":"Eindhoven, The Netherlands 1","department":["Department of Cardiology, Catharina Hospital"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-0522-667X","authenticated-orcid":true,"given":"Carlijn M. A.","family":"Buck","sequence":"additional","affiliation":[{"name":"Eindhoven, The Netherlands 2","department":["Department of Biomedical Engineering, Eindhoven University of Technology"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-5006-0111","authenticated-orcid":false,"given":"Marcel","family":"van \u2018t Veer","sequence":"additional","affiliation":[{"name":"Eindhoven, The Netherlands 1","department":["Department of Cardiology, Catharina Hospital"]},{"name":"Eindhoven, The Netherlands 2","department":["Department of Biomedical Engineering, Eindhoven University of Technology"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-0779-4785","authenticated-orcid":false,"given":"Wouter","family":"Huberts","sequence":"additional","affiliation":[{"name":"Eindhoven, The Netherlands 2","department":["Department of Biomedical Engineering, Eindhoven University of Technology"]},{"name":"Maastricht, The Netherlands 3","department":["Department of Biomedical Engineering, CARIM School for Cardiovascular Diseases, Maastricht University"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-4084-2064","authenticated-orcid":true,"given":"Frans N.","family":"van de Vosse","sequence":"additional","affiliation":[{"name":"Eindhoven, The Netherlands 2","department":["Department of Biomedical Engineering, Eindhoven University of Technology"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-8166-3716","authenticated-orcid":false,"given":"Lukas R. 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