@article{61e979c6831349cc89effe67f7f86ddc,
title = "The 'Digital Twin' to enable the vision of precision cardiology",
abstract = "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.",
keywords = "ARTIFICIAL-INTELLIGENCE, Artificial intelligence, BIG DATA, BLOOD-FLOW, CT ANGIOGRAPHY, Computational modelling, Digital twin, HEART, INFORMATION, MEDICINE, PERFORMANCE, PRESSURE, Precision medicine, RISK, TRIAL, CHANNEL",
author = "Jorge Corral-Acero and Francesca Margara and Maciej Marciniak and Cristobal Rodero and Filip Loncaric and Yingjing Feng and Andrew Gilbert and Fernandes, {Joao F.} and Bukhari, {Hassaan A.} and Ali Wajdan and Martinez, {Manuel Villegas} and Santos, {Mariana Sousa} and Mehrdad Shamohammdi and Hongxing Luo and Philip Westphal and Paul Leeson and Paolo DiAchille and Viatcheslav Gurev and Manuel Mayr and Liesbet Geris and Pras Pathmanathan and Tina Morrison and Richard Cornelussen and Frits Prinzen and Tammo Delhaas and Ada Doltra and Marta Sitges and Vigmond, {Edward J.} and Ernesto Zacur and Vicente Grau and Blanca Rodriguez and Remme, {Espen W.} and Steven Niederer and Peter Mortier and Kristin McLeod and Mark Potse and Esther Pueyo and Alfonso Bueno-Orovio and Pablo Lamata",
note = "Funding Information: This work was supported by the EU's Horizon 2020 Marie Sklodowska- Curie ITN Projects (g.a. 764738 and 766082), the EU's Horizon 2020 research and innovation programme (g.a. 675451 and 823712), the Wellcome/EPSRC Centre for Medical Engineering (WT 203148/Z/16/Z), the National Research Agency (ANR) (g.a. ANR-10-IAHU-04), the NC3RS (NC/P001076/1) and the British Heart Foundation (RE/13/2/ 30182, RE/13/1/30181, TG/17/3/33406, PG/16/75/32383, FS/17/22/ 32644, CH/16/3/21406, RG/16/14/32397). E.Pueyo holds an ERC Starting Grant (g.a. 638284). B. Rodriguez and P.Lamata hold Wellcome Trust Senior Research Fellowships (214290/Z/18/Z, 209450/Z/17/Z). Publisher Copyright: {\textcopyright} The Author(s) 2020.",
year = "2020",
month = dec,
day = "21",
doi = "10.1093/eurheartj/ehaa159",
language = "English",
volume = "41",
pages = "4556--4564",
journal = "European Heart Journal",
issn = "0195-668X",
publisher = "Oxford University Press",
number = "48",
}