54 citations · 64 across the 10 of their papers we have counts for
11 papers
Physiology and Anatomy Aware Inverse Inference of Myocardial Infarction for Cardiac Digital Twin
Mengxiao Wang, Yilin Lyu, Julia Camps +6
Accurate localization of myocardial infarction is essential for risk stratification. While LGE-MRI remains the gold standard, it is resource-intensive. Integrating cine MRI with EC…
Simulation-based digital twinning of activation and repolarisation sequences from the ECG across healthy and diseased hearts
James A Coleman, Julia Camps, Abdallah I Hasaballa +1
Abnormal patterns of ventricular repolarisation contribute to lethal arrhythmias in various cardiac conditions, including inherited and acquired channelopathies, cardiomyopathies,…
An Automated Computational Pipeline for Generating Large-Scale Cohorts of Patient-Specific Ventricular Models in Electromechanical In Silico Trials
Ruben Doste, Julia Camps, Zhinuo Jenny Wang +8
In recent years, human in silico trials have gained significant traction as a powerful approach to evaluate the effects of drugs, clinical interventions, and medical devices. In si…
Personalized Topology-Informed Localization of Standard 12-Lead ECG Electrode Placement from Incomplete Cardiac MRIs for Efficient Cardiac Digital Twins
Lei Li, Hannah Smith, Yilin Lyu +5
Cardiac digital twins (CDTs) offer personalized in-silico cardiac representations for the inference of multi-scale properties tied to cardiac mechanisms. The creation of CDTs requi…
Solving the Inverse Problem of Electrocardiography for Cardiac Digital Twins: A Survey
Lei Li, Julia Camps, Blanca Rodriguez +1
Cardiac digital twins (CDTs) are personalized virtual representations used to understand complex cardiac mechanisms. A critical component of CDT development is solving the ECG inve…
Cardiac Digital Twin Pipeline for Virtual Therapy Evaluation
Julia Camps, Zhinuo Jenny Wang, Ruben Doste +6
Cardiac digital twins are computational tools capturing key functional and anatomical characteristics of patient hearts for investigating disease phenotypes and predicting response…
Towards Enabling Cardiac Digital Twins of Myocardial Infarction Using Deep Computational Models for Inverse Inference
Lei Li, Julia Camps, Zhinuo +5
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 d…
Digital Twinning of the Human Ventricular Activation Sequence to Clinical 12-lead ECGs and Magnetic Resonance Imaging Using Realistic Purkinje Networks for in Silico Clinical Trials
Julia Camps, Lucas Arantes Berg, Zhinuo Jenny Wang +12
Cardiac in silico clinical trials can virtually assess the safety and efficacy of therapies using human-based modelling and simulation. These technologies can provide mechanistic e…
Influence of Myocardial Infarction on QRS Properties: A Simulation Study
Lei Li, Julia Camps, Zhinuo +4
The interplay between structural and electrical changes in the heart after myocardial infarction (MI) plays a key role in the initiation and maintenance of arrhythmia. The anatomic…
Deep Computational Model for the Inference of Ventricular Activation Properties
Lei Li, Julia Camps, Abhirup Banerjee +3
Patient-specific cardiac computational models are essential for the efficient realization of precision medicine and in-silico clinical trials using digital twins. Cardiac digital t…
Inference of ventricular activation properties from non-invasive electrocardiography
Julia Camps, Brodie Lawson, Christopher Drovandi +5
The realisation of precision cardiology requires novel techniques for the non-invasive characterisation of individual patients' cardiac function to inform therapeutic and diagnosti…