Towards enabling cardiac digital twins of myocardial infarction using deep computational models for inverse inference
Cardiac digital twins (CDTs) have the potential to offer individualized evaluation of cardiac
function in a non-invasive manner, making them a promising approach for personalized …
function in a non-invasive manner, making them a promising approach for personalized …
[HTML][HTML] Inference of ventricular activation properties from non-invasive electrocardiography
The realisation of precision cardiology requires novel techniques for the non-invasive
characterisation of individual patients' cardiac function to inform therapeutic and diagnostic …
characterisation of individual patients' cardiac function to inform therapeutic and diagnostic …
Deep computational model for the inference of ventricular activation properties
Patient-specific cardiac computational models are essential for the efficient realization of
precision medicine and in-silico clinical trials using digital twins. Cardiac digital twins can …
precision medicine and in-silico clinical trials using digital twins. Cardiac digital twins can …
[HTML][HTML] A framework for the generation of digital twins of cardiac electrophysiology from clinical 12-leads ECGs
Abstract Cardiac digital twins (Cardiac Digital Twin (CDT) s) of human electrophysiology
(Electrophysiology (EP)) are digital replicas of patient hearts derived from clinical data that …
(Electrophysiology (EP)) are digital replicas of patient hearts derived from clinical data that …
Cardiac Digital Twin Pipeline for Virtual Therapy Evaluation
Cardiac digital twins are computational tools capturing key functional and anatomical
characteristics of patient hearts for investigating disease phenotypes and predicting …
characteristics of patient hearts for investigating disease phenotypes and predicting …
Quantifying variabilities in cardiac digital twin models of the electrocardiogram
CDT of human cardiac EP are digital replicas of patient hearts that match like-for-like clinical
observations. The ECG, as the most prevalent non-invasive observation of cardiac …
observations. The ECG, as the most prevalent non-invasive observation of cardiac …
[HTML][HTML] Harnessing 12-lead ECG and MRI data to personalise repolarisation profiles in cardiac digital twin models for enhanced virtual drug testing
Cardiac digital twins are computational tools capturing key functional and anatomical
characteristics of patient hearts for investigating disease phenotypes and predicting …
characteristics of patient hearts for investigating disease phenotypes and predicting …
HDL: Hybrid deep learning for the synthesis of myocardial velocity maps in digital twins for cardiac analysis
Synthetic digital twins based on medical data accelerate the acquisition, labelling and
decision making procedure in digital healthcare. A core part of digital healthcare twins is …
decision making procedure in digital healthcare. A core part of digital healthcare twins is …
Parameter subset reduction for imaging-based digital twin generation of patients with left ventricular mechanical discoordination
Background Integration of a patient's non-invasive imaging data in a digital twin (DT) of the
heart can provide valuable insight into the myocardial disease substrates underlying left …
heart can provide valuable insight into the myocardial disease substrates underlying left …
Deep learning-based emulation of human cardiac activation sequences
The vision of digital twins for precision cardiology is to combine expert knowledge and data
of patients' cardiac pathophysiology with advanced computational methods, in order to …
of patients' cardiac pathophysiology with advanced computational methods, in order to …