The 'Digital Twin' to enable the vision of precision cardiology
Jorge Corral-Acero
(1)
,
Francesca Margara
(2)
,
Maciej Marciniak
(3)
,
Cristobal Rodero
(3)
,
Filip Loncaric
(4)
,
Yingjing Feng
(5)
,
Andrew Gilbert
(6)
,
Joao F Fernandes
(3)
,
Hassaan A Bukhari
(7, 8)
,
Ali Wajdan
(6)
,
Manuel Villegas Martinez
(6)
,
Mariana Sousa Santos
(9)
,
Mehrdad Shamohammdi
(10)
,
Hongxing Luo
(10)
,
Philip Westphal
(11)
,
Paul Leeson
(12)
,
Paolo Diachille
(13)
,
Viatcheslav Gurev
(13)
,
Manuel Mayr
(3)
,
Liesbet Geris
(14)
,
Pras Pathmanathan
(15)
,
Tina Morrison
(15)
,
Richard Cornelussen
(11)
,
Frits Prinzen
(16)
,
Tammo Delhaas
(16)
,
Ada Doltra
(17)
,
Marta Sitges
(17)
,
Edward J Vigmond
(5, 8)
,
Ernesto Zacur
(18)
,
Vicente Grau
(1)
,
Blanca Rodriguez
(2)
,
Espen W Remme
(19)
,
Steven Niederer
(3)
,
Peter Mortier
(9)
,
Kristin Mcleod
(20)
,
Mark Potse
(21, 22, 8)
,
Esther Pueyo
(7, 23)
,
Alfonso Bueno-Orovio
(2)
,
Pablo Lamata
(3)
1
Department of Engineering Science [Oxford]
2 Department of Computer Science [Oxford]
3 King‘s College London
4 UB - Universitat de Barcelona
5 IHU Liryc - Institut de rythmologie et modélisation cardiaque [Pessac]
6 Oslo University Hospital [Oslo]
7 I3A - Aragón Institute of Engineering Research [Zaragoza]
8 IMB - Institut de Mathématiques de Bordeaux
9 FEops
10 Maastricht University [Maastricht]
11 Medtronic Bakken Research Center BV
12 John Radcliffe Hospital [Oxford University Hospital]
13 IBM Thomas J. Watson Research Center
14 VPH - Virtual Physiological Human Institute [Leuven]
15 FDA - U.S. Food and Drug Administration
16 CARIM - Cardiovascular Research Institute Maastricht
17 IDIBAPS - Institut d'Investigacions Biomèdiques August Pi i Sunyer
18 University of Oxford
19 UiO - University of Oslo
20 GE Vingmed Ultrasound AS
21 IHU-LIRYC
22 CARMEN - Modélisation et calculs pour l'électrophysiologie cardiaque
23 CIBER-BBN - Biomedical Research Networking Center in Bioengineering, Biomaterials and Nanomedicine
2 Department of Computer Science [Oxford]
3 King‘s College London
4 UB - Universitat de Barcelona
5 IHU Liryc - Institut de rythmologie et modélisation cardiaque [Pessac]
6 Oslo University Hospital [Oslo]
7 I3A - Aragón Institute of Engineering Research [Zaragoza]
8 IMB - Institut de Mathématiques de Bordeaux
9 FEops
10 Maastricht University [Maastricht]
11 Medtronic Bakken Research Center BV
12 John Radcliffe Hospital [Oxford University Hospital]
13 IBM Thomas J. Watson Research Center
14 VPH - Virtual Physiological Human Institute [Leuven]
15 FDA - U.S. Food and Drug Administration
16 CARIM - Cardiovascular Research Institute Maastricht
17 IDIBAPS - Institut d'Investigacions Biomèdiques August Pi i Sunyer
18 University of Oxford
19 UiO - University of Oslo
20 GE Vingmed Ultrasound AS
21 IHU-LIRYC
22 CARMEN - Modélisation et calculs pour l'électrophysiologie cardiaque
23 CIBER-BBN - Biomedical Research Networking Center in Bioengineering, Biomaterials and Nanomedicine
Mark Potse
- Function : Author
- PersonId : 4304
- IdHAL : markpotse
- ORCID : 0000-0003-4166-2687
- IdRef : 22822246X
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.
Origin : Files produced by the author(s)