99069 20230330095434.0 doi 10.1093/eurheartj/ehaa159 sideral 122375 ART-2020-122375 eng Corral-Acero, J. The ''Digital Twin'' to enable the vision of precision cardiology 2020 Access copy available to the general public Unrestricted Providing therapies tailored to each patient is the vision of precision medicine, enabled by the increasing ability to capture extensive data about individual patients. In this position paper, we argue that the second enabling pillar towards this vision is the increasing power of computers and algorithms to learn, reason, and build the ''digital twin'' of a patient. Computational models are boosting the capacity to draw diagnosis and prognosis, and future treatments will be tailored not only to current health status and data, but also to an accurate projection of the pathways to restore health by model predictions. The early steps of the digital twin in the area of cardiovascular medicine are reviewed in this article, together with a discussion of the challenges and opportunities ahead. We emphasize the synergies between mechanistic and statistical models in accelerating cardiovascular research and enabling the vision of precision medicine. info:eu-repo/grantAgreement/EC/H2020/675451/EU/A Centre of Excellence in Computational Biomedicine/CompBioMed This project has received funding from the European Union’s Horizon 2020 research and innovation program under grant agreement No H2020 675451-CompBioMed info:eu-repo/grantAgreement/EC/H2020/764738/EU/Personalised In-Silico Cardiology/PIC This project has received funding from the European Union’s Horizon 2020 research and innovation program under grant agreement No H2020 764738-PIC info:eu-repo/grantAgreement/EC/H2020/766082/EU/MultidisciplinarY training network for ATrial fibRillation monItoring, treAtment and progression/MY-ATRIA This project has received funding from the European Union’s Horizon 2020 research and innovation program under grant agreement No H2020 766082-MY-ATRIA info:eu-repo/grantAgreement/EC/H2020/823712/EU/A Centre of Excellence in Computational Biomedicine/CompBioMed2 This project has received funding from the European Union’s Horizon 2020 research and innovation program under grant agreement No H2020 823712-CompBioMed2 info:eu-repo/semantics/openAccess by http://creativecommons.org/licenses/by/3.0/es/ 29.983 2020 CARDIAC & CARDIOVASCULAR SYSTEMS 2 / 141 = 0.014 2020 Q1 T1 4.336 2020 Cardiology and Cardiovascular Medicine 2020 Q1 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion Margara, F. Marciniak, M. Rodero, C. Loncaric, F. Feng, Y. Gilbert, A. Fernandes, J.F. Bukhari, H.A. Universidad de Zaragoza (orcid)0000-0001-5976-0483 Wajdan, A. Martinez, M.V. Santos, M.S. Shamohammdi, M. Luo, H. Westphal, P. Leeson, P. DiAchille, P. Gurev, V. Mayr, M. Geris, L. Pathmanathan, P. Morrison, T. Cornelussen, R. Prinzen, F. Delhaas, T. Doltra, A. Sitges, M. Vigmond, E.J. Zacur, E. Grau, V. Rodriguez, B. Remme, E.W. Niederer, S. Mortier, P. McLeod, K. Potse, M. Pueyo, E. Universidad de Zaragoza (orcid)0000-0002-1960-407X Bueno-Orovio, A. Lamata, P. 5008 800 Universidad de Zaragoza Dpto. Ingeniería Electrón.Com. Área Teoría Señal y Comunicac. 41, 48 (2020), 4556-4564 Eur. heart j. European heart journal 0195-668X 1790208 http://zaguan.unizar.es/record/99069/files/texto_completo.pdf Versión publicada 2646516 http://zaguan.unizar.es/record/99069/files/texto_completo.jpg?subformat=icon icon Versión publicada oai:zaguan.unizar.es:99069 articulos driver 2023-03-30-09:42:16 ARTICLE