The 'Digital Twin' to enable the vision of precision cardiology

Autor: Pras Pathmanathan, Liesbet Geris, Yingjing Feng, Francesca Margara, Andrew Gilbert, Espen W. Remme, Alfonso Bueno-Orovio, Joao Filipe Fernandes, Mark Potse, Marta Sitges, Blanca Rodriguez, Viatcheslav Gurev, Tammo Delhaas, Tina M. Morrison, Manuel Villegas Martinez, Pablo Lamata, Ali Wajdan, Ada Doltra, Filip Loncaric, Hassaan A. Bukhari, Richard Cornelussen, Paul Leeson, Paolo DiAchille, Frits W. Prinzen, Peter Mortier, Manuel Mayr, Hongxing Luo, Edward J. Vigmond, Mehrdad Shamohammdi, Esther Pueyo, Kristin McLeod, Philip Westphal, Vicente Grau, Jorge Corral-Acero, Ernesto Zacur, Steven A. Niederer, Mariana Sousa Santos, Maciej Marciniak, Cristobal Rodero
Přispěvatelé: Department of Engineering Science [Oxford], Institute of Biomedical Engineering [Oxford] (IBME), University of Oxford [Oxford]-University of Oxford [Oxford], Department of Computer Science [Oxford], University of Oxford [Oxford], King‘s College London, Universitat de Barcelona (UB), Institut de rythmologie et modélisation cardiaque [Pessac] (IHU Liryc), Oslo University Hospital [Oslo], Aragón Institute of Engineering Research [Zaragoza] (I3A), University of Zaragoza - Universidad de Zaragoza [Zaragoza], Institut de Mathématiques de Bordeaux (IMB), Université Bordeaux Segalen - Bordeaux 2-Université Sciences et Technologies - Bordeaux 1-Université de Bordeaux (UB)-Institut Polytechnique de Bordeaux (Bordeaux INP)-Centre National de la Recherche Scientifique (CNRS), FEops, Maastricht University [Maastricht], Medtronic Bakken Research Center BV, John Radcliffe Hospital [Oxford University Hospital], IBM Thomas J. Watson Research Center, IBM, Virtual Physiological Human Institute [Leuven] (VPH), U.S. Food and Drug Administration (FDA), Cardiovascular Research Institute Maastricht (CARIM), Institut d'Investigacions Biomèdiques August Pi i Sunyer (IDIBAPS), University of Oslo (UiO), GE Vingmed Ultrasound AS, IHU-LIRYC, CHU Bordeaux [Bordeaux]-Université Bordeaux Segalen - Bordeaux 2, Modélisation et calculs pour l'électrophysiologie cardiaque (CARMEN), Université Bordeaux Segalen - Bordeaux 2-Université Sciences et Technologies - Bordeaux 1-Université de Bordeaux (UB)-Institut Polytechnique de Bordeaux (Bordeaux INP)-Centre National de la Recherche Scientifique (CNRS)-Université Bordeaux Segalen - Bordeaux 2-Université Sciences et Technologies - Bordeaux 1-Université de Bordeaux (UB)-Institut Polytechnique de Bordeaux (Bordeaux INP)-Centre National de la Recherche Scientifique (CNRS)-Inria Bordeaux - Sud-Ouest, Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria)-IHU-LIRYC, CHU Bordeaux [Bordeaux]-Université Bordeaux Segalen - Bordeaux 2-CHU Bordeaux [Bordeaux], Biomedical Research Networking Center in Bioengineering, Biomaterials and Nanomedicine (CIBER-BBN), Instituto de Salud Carlos III [Madrid] (ISC)-ministerio de ciencia e innovacion, 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 (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), theNC3RS (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 StartingGrant (g.a. 638284). B. Rodriguez and P. Lamata hold Wellcome TrustSenior Research Fellowships (214290/Z/18/Z, 209450/Z/17/Z)., ANR-10-IAHU-04/10-IAHU-0004,LIRYC,L'Institut de Rythmologie et modélisation Cardiaque(2010), ANR-10-IAHU-0004,LIRYC,L'Institut de Rythmologie et modélisation Cardiaque(2010), Université Bordeaux Segalen - Bordeaux 2-CHU Bordeaux [Bordeaux], Université Bordeaux Segalen - Bordeaux 2-CHU Bordeaux [Bordeaux]-Université Bordeaux Segalen - Bordeaux 2-CHU Bordeaux [Bordeaux]-Institut de Mathématiques de Bordeaux (IMB), Université Bordeaux Segalen - Bordeaux 2-Université Sciences et Technologies - Bordeaux 1-Université de Bordeaux (UB)-Institut Polytechnique de Bordeaux (Bordeaux INP)-Centre National de la Recherche Scientifique (CNRS)-Université Sciences et Technologies - Bordeaux 1-Université de Bordeaux (UB)-Institut Polytechnique de Bordeaux (Bordeaux INP)-Centre National de la Recherche Scientifique (CNRS)-Inria Bordeaux - Sud-Ouest, Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria), University of Oxford-University of Oxford, University of Oxford, Université Bordeaux Segalen - Bordeaux 2-Université Sciences et Technologies - Bordeaux 1 (UB)-Université de Bordeaux (UB)-Institut Polytechnique de Bordeaux (Bordeaux INP)-Centre National de la Recherche Scientifique (CNRS), Université Bordeaux Segalen - Bordeaux 2-Université Sciences et Technologies - Bordeaux 1 (UB)-Université de Bordeaux (UB)-Institut Polytechnique de Bordeaux (Bordeaux INP)-Centre National de la Recherche Scientifique (CNRS)-Université Bordeaux Segalen - Bordeaux 2-Université Sciences et Technologies - Bordeaux 1 (UB)-Université de Bordeaux (UB)-Institut Polytechnique de Bordeaux (Bordeaux INP)-Centre National de la Recherche Scientifique (CNRS)-Inria Bordeaux - Sud-Ouest, Université Bordeaux Segalen - Bordeaux 2-CHU Bordeaux [Bordeaux]-CHU Bordeaux [Bordeaux]
Jazyk: angličtina
Rok vydání: 2020
Předmět:
Artificial intelligence
Cardiac & Cardiovascular Systems
INFORMATION
diagnosis
030204 cardiovascular system & hematology
0302 clinical medicine
CHANNEL
Medicine
AcademicSubjects/MED00200
RISK
0303 health sciences
Computational model
ARTIFICIAL-INTELLIGENCE
Precision medicine
twins
3. Good health
cardiology
HEART
TRIAL
Cardiology and Cardiovascular Medicine
Life Sciences & Biomedicine
Algorithms
Digital Health and Innovation
vision
Boosting (machine learning)
BIG DATA
Cardiovascular research
MEDLINE
PRESSURE
03 medical and health sciences
models
[SDV.MHEP.CSC]Life Sciences [q-bio]/Human health and pathology/Cardiology and cardiovascular system
computer simulation
Extensive data
State of the Art Review
Humans
030304 developmental biology
Science & Technology
BLOOD-FLOW
business.industry
MEDICINE
Statistical model
PERFORMANCE
CT ANGIOGRAPHY
Data science
Digital twin
Computational modelling
Cardiovascular System & Cardiology
Position paper
precision
business
statistical
Zdroj: European Heart Journal Supplements
European Heart Journal Supplements, Oxford University Press (OUP), In press, pp.1-11. ⟨10.1093/eurheartj/ehaa159⟩
INRIA a CCSD electronic archive server
Mémoires en Sciences de l'Information et de la Communication
Hal-Diderot
Recolector de Ciencia Abierta, RECOLECTA
UnpayWall
ORCID
Microsoft Academic Graph
PubMed Central
Hyper Article en Ligne
Lirias
Oskar Bordeaux
Sygma
NARCIS
Digital Repository of University of Zaragoza
European Heart Journal, Oxford University Press (OUP): Policy B, 2020, 41 (48), pp.4556-4564. ⟨10.1093/eurheartj/ehaa159⟩
Universidad de Zaragoza
Zaguán: Repositorio Digital de la Universidad de Zaragoza
European Heart Journal
European Heart Journal, 2020, 41 (48), pp.4556-4564. ⟨10.1093/eurheartj/ehaa159⟩
Zaguán. Repositorio Digital de la Universidad de Zaragoza
instname
ISSN: 1520-765X
0195-668X
1522-9645
Popis: 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. ispartof: EUROPEAN HEART JOURNAL vol:41 issue:48 pages:4556-+ ispartof: location:England status: published
Databáze: OpenAIRE
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