Efficient Ventricular Parameter Estimation Using AI-Surrogate Models.

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Title

Efficient Ventricular Parameter Estimation Using AI-Surrogate Models.

Content partner

The University of Auckland Library

Collection

ResearchSpace@Auckland

Description

The onset and progression of pathological heart conditions, such as cardiomyopathy or heart failure, affect its mechanical behaviour due to the remodelling of the myocardial tissues to preserve its functional response. Identification of the constitutive properties of heart tissues could provide useful biomarkers to diagnose and assess the progression of disease. We have previously demonstrated the utility of efficient AI-surrogate models to simulate passive cardiac mechanics. Here, we propose...

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Format

Research paper

Research format

Journal article

Date created

2021-1

Creator

Maso Talou, Gonzalo D / Babarenda Gamage, Thiranja P / Nash, Martyn P

URL

https://hdl.handle.net/2292/58764

Related subjects

MLP / cardiac mechanics / optimisation / parameter estimation / surrogate model / Science & Technology / Life Sciences & Biomedicine / Physiology / STIFFNESS / MECHANICS / PHYSICS / DENSE / 0606 Physiology / 1116 Medical Physiology / 1701 Psychology

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