Cardiac computational modelling
نویسندگان
چکیده
Cardiovascular diseases currently have a major social and economic impact, constituting one of the leading causes mortality morbidity. Personalized computational models heart are demonstrating their usefulness both to help understand mechanisms underlying cardiac disease, optimize treatment predict patient's response. Within this framework, Spanish Research Network for Cardiac Computational Modelling (VHeart-SN) has been launched. The general objective VHeart-SN network is development an integrated, modular multiscale multiphysical model heart. This addressed through following specific objectives: a) integrate different numerical methods taking into account specificity patients; b) assist in advancing knowledge associated with vascular diseases; c) support application personalized therapies. article presents current state modelling scientific works conducted by members gain greater understanding characteristics these models. Las enfermedades cardiovasculares tienen en la actualidad un gran impacto y económico constituyen una de las principales causas mortalidad morbilidad. Los modelos computacionales personalizados del corazón están demostrando ser útiles tanto para ayudar comprender los mecanismos subyacentes patologías cardiacas como optimizar su tratamiento prediciendo respuesta paciente. En este contexto, se ha puesto marcha Red Española Investigación Modelización Computacional Cardiaca (V-Heart SN). El objetivo V-Heart SN es el desarrollo modelo computacional multifísico multiescala integrado corazón. Este aborda través siguientes objetivos específicos: integrar diferentes numéricos teniendo cuenta especificidad pacientes; avanzar conocimiento asociados vasculares; apoyar aplicación terapias personalizadas. artículo presenta estado actual modelización cardiaca trabajos científicos desarrollados por miembros red favorecer mayor comprensión características utilidad modelos.
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ژورنال
عنوان ژورنال: Revista española de cardiología
سال: 2021
ISSN: ['1885-5857']
DOI: https://doi.org/10.1016/j.rec.2020.05.024