Data-Driven Cardiovascular Modeling is a computational modeling approach within cardiovascular system modeling that uniquely integrates empirical physiological data to infer, calibrate, and validate model parameters and structures, distinguishing itself from mechanistic or hypothesis-driven models by prioritizing data-derived insights to represent cardiovascular function and dynamics.
76
Publications
3.5K
Citations
413
Authors
200
Institutions
Publications per year
2017–2026
47
Publications
76
The ‘Digital Twin’ to enable the vision of precision cardiology
Jorge Corral Acero, Francesca Margara, M Marciniak et al. · European Heart Journal · 2020 · 823 citations · Full text
1–5 of 76
Authors
413
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1–5 of 413
Institutions
200
King's College London
London, United Kingdom
7 h-index
24 publications
6.2K citations
University of Oxford
Oxford, United Kingdom
6 h-index
30 publications
7K citations
University of Sheffield
Sheffield, United Kingdom
5 h-index
10 publications
496 citations
Politecnico di Milano
Milan, Italy
4 h-index
8 publications
274 citations
University of Maryland, College Park
College Park, United States
3 h-index
7 publications
95 citations
University College London
London, United Kingdom
3 h-index
12 publications
418 citations
Center for Devices and Radiological Health
Rockville, United States
3 h-index
4 publications
1.8K citations
Stanford University
Stanford, United States
3 h-index
6 publications
192 citations
1–8 of 200
Venues
- Computer Methods in Applied Mechanics and Engineering
4 publications · 170 citations
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- Biomedical Signal Processing and Control
4 publications · 262 citations
4
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- Computers in Biology and Medicine
4 publications · 252 citations
4
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- Computer Methods and Programs in Biomedicine
3 publications · 63 citations
3
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- International Journal for Numerical Methods in Biomedical Engineering
3 publications · 69 citations
3
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1–5