ArticleFrontiers in physiology2013
Ensuring reliability of safety-critical clinical applications of computational cardiac models.
Article in Frontiers in physiology, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 28 papers.
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Who cites it
28 citing papers in PubMed.
- Up digital and personal: How heart digital twins can transform heart patient care.Heart rhythm · 2024Review
- A Quantitative Systems Pharmacology Perspective on the Importance of Parameter Identifiability.Bulletin of mathematical biology · 2022Article
- Mechanical Regulation of Limb Bud Formation.Cells · 2022Review
- The 'Digital Twin' to enable the vision of precision cardiology.European heart journal · 2020Article
- Translational applications of computational modelling for patients with cardiac arrhythmias.Heart (British Cardiac Society) · 2020Review
- Calibration of ionic and cellular cardiac electrophysiology models.Wiley interdisciplinary reviews. Systems biology and medicine · 2020Review
- Considering discrepancy when calibrating a mechanistic electrophysiology model.Philosophical transactions. Series A, Mathematical, physical, and engineering sciences · 2020Article
- In Silico Methods for Development of Generic Drug-Device Combination Orally Inhaled Drug Products.CPT: pharmacometrics & systems pharmacology · 2019Review
- A demonstration of modularity, reuse, reproducibility, portability and scalability for modeling and simulation of cardiac electrophysiology using Kepler Workflows.PLoS computational biology · 2019Article
- Comprehensive Uncertainty Quantification and Sensitivity Analysis for Cardiac Action Potential Models.Frontiers in physiology · 2019Article
- Reproducible model development in the cardiac electrophysiology Web Lab.Progress in biophysics and molecular biology · 2018Article
- Sinusoidal voltage protocols for rapid characterisation of ion channel kinetics.The Journal of physiology · 2018Article
- The Use of Computational Modeling and Simulation to Create Virtual Patients: Application to Cardiac Pacing and Defibrillation Systems.Journal of cardiovascular translational research · 2018Article
- Patient-Specific Cardiovascular Computational Modeling: Diversity of Personalization and Challenges.Journal of cardiovascular translational research · 2018Review
- In silico clinical trials for pediatric orphan diseases.Scientific reports · 2018Article
- Validation and Trustworthiness of Multiscale Models of Cardiac Electrophysiology.Frontiers in physiology · 2018Review
- Uncertainty Quantification Reveals the Importance of Data Variability and Experimental Design Considerations forFrontiers in physiology · 2017Article
- I love it when a plan comes together: Insight gained through convergence of competing mathematical models.Journal of molecular and cellular cardiology · 2017Article
- Using physiologically based models for clinical translation: predictive modelling, data interpretation or something in-between?The Journal of physiology · 2016Review
- A Parsimonious Model of the Rabbit Action Potential Elucidates the Minimal Physiological Requirements for Alternans and Spiral Wave Breakup.PLoS computational biology · 2016Article
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Authors and funding
2 authors.
Funding
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Abstract
Computational models of cardiac electrophysiology have been used for over half a century to investigate physiological mechanisms and generate hypotheses for experimental testing, and are now starting to play a role in clinical applications. There is currently a great deal of interest in using models as diagnostic or therapeutic aids, for example using patient-specific whole-heart simulations to optimize cardiac resynchronization therapy, ablation therapy, and defibrillation. However, if models are to be used in safety-critical clinical decision making, the reliability of their predictions needs to be thoroughly investigated. In engineering and the physical sciences, the field of "verification, validation and uncertainty quantification" (VVUQ) [also known as "verification and validation" (V&V)] has been developed for rigorously evaluating the credibility of computational model predictions. In this article we first discuss why it is vital that cardiac models be developed and evaluated within a VVUQ framework, and then consider cardiac models in the context of each of the stages in VVUQ. We identify some of the major difficulties which may need to be overcome for cardiac models to be used in safely-critical clinical applications.
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