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Cardiac computational modelling

  • Jean R. Bragard
  • , Oscar Camara
  • , Blas Echebarria
  • , Luca Gerardo-Giorda
  • , Esther Pueyo
  • , Javier Saiz
  • , Rafael Sebastián
  • , Eduardo Soudah
  • , Mariano Vázquez

Research output: Contribution to journalArticlepeer-review

Abstract

Cardiovascular diseases currently have a major social and economic impact, constituting one of the leading causes of mortality and morbidity. Personalized computational models of the heart are demonstrating their usefulness both to help understand the mechanisms underlying cardiac disease, and to optimize their treatment and predict the patient's response. Within this framework, the Spanish Research Network for Cardiac Computational Modelling (VHeart-SN) has been launched. The general objective of the VHeart-SN network is the development of an integrated, modular and multiscale multiphysical computational model of the heart. This general objective is addressed through the following specific objectives: a) to integrate the different numerical methods and models taking into account the specificity of patients; b) to assist in advancing knowledge of the mechanisms associated with cardiac and vascular diseases; and c) to support the application of different personalized therapies. This article presents the current state of cardiac computational modelling and different scientific works conducted by the members of the network to gain greater understanding of the characteristics and usefulness of these models.
Original languageEnglish
Pages (from-to)65-71
Number of pages7
JournalRevista Española de Cardiología (English Edition)
Volume74
Issue number1
DOIs
Publication statusPublished - Jan 2021

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

  1. SDG 3 - Good Health and Well-being
    SDG 3 Good Health and Well-being

Fields of science

  • 101 Mathematics
  • 101013 Mathematical logic
  • 101024 Probability theory
  • 102001 Artificial intelligence
  • 102003 Image processing
  • 102019 Machine learning
  • 102035 Data science
  • 603109 Logic
  • 202027 Mechatronics

JKU Focus areas

  • Digital Transformation

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