Digital Twins for Heart Faliure Diagnosis
Modelling pipeline integrating echocardiography, shear‑wave elastography, and hybrid physics/data‑driven models, delivering a validated decision‑support tool for early detection of heart‑failure pathology.
This project is part of my post-doctoral research activities with the Division of Biomechanics at Norwegian University of Science and Technology (NTNU), Trondheim, Norway. The project is in collaboration with the Department of Cardiovascular Scienecs at KU Leuven, Belgium.
As the manuscript is under review, I will not be able to disclose the details of the project in public domain at the moment. The details will be updated as soon as the manuscript is accepted for publication.
What I am trying to build though this project to to answer the following question: How to build measurement-supported model predictive controls to intervene patient outcome?
A potential digital twin framework that utilises structral information (echocardiography), material information (shear wave elastography) to estimate functional information of the Left Ventricle. An explanable and clinicaly interpretable model to reconstrcut LV PV loop and estimate LV filling pressure for diastiloc dysfunction diagnosis.
I will be presenting some of the results in the upcoming 17th World Congress on Compuational Mechanics Conference, to be held in July 2026, Munich.
More details to be updated soon.
