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Multiscale Cohort Modeling of Atrial Electrophysiology : Risk Stratification for Atrial Fibrillation through Machine Learning on Electrocardiograms
An early detection and diagnosis of atrial fibrillation sets the course for timely intervention to prevent potentially occurring comorbidities. Electrocardiogram data resulting from electrophysiological cohort modeling and simulation can be a valuable data resource for improving automated atrial fibrillation risk stratification with machine learning techniques and thus, reduces the risk of stroke in affected patients.
A Multiscale In Silico Study to Characterize the Atrial Electrical Activity of Patients With Atrial Fibrillation : A Translational Study to Guide Ablation Therapy
The atrial substrate undergoes electrical and structural remodeling during atrial fibrillation. Detailed multiscale models were used to study the effect of structural remodeling induced at the cellular and tissue levels. Simulated electrograms were used to train a machine-learning algorithm to characterize the substrate. Also, wave propagation direction was tracked from unannotated electrograms. In conclusion, in silico experiments provide insight into electrograms' information of the substrate.
Death in the Doldrums
With their very long range, the giant Type IX U-Cruisers gave Admiral Dnitz's U-boat fleet global reach. Initially these boats operated with considerable success off the East coast of America and in the Caribbean but their main impact was in the Gulf of Guinea 1942-43 which, due to the closure of the Suez Canal, was a vital Allied supply route. Two submarines in particular (U-68 and U-505) had a profound effect causing major panic by their hugely successful operations.
Multiscale Modeling of Cardiac Electrophysiology: Adaptation to Atrial and Ventricular Rhythm Disorders and Pharmacological Treatment
Multiscale modeling of cardiac electrophysiology helps to better understand the underlying mechanisms of atrial fibrillation, acute cardiac ischemia and pharmacological treatment. For this purpose, measurement data reflecting these conditions have to be integrated into models of cardiac electrophysiology. Several methods for this model adaptation are introduced in this thesis. The resulting effects are investigated in multiscale simulations ranging from the ion channel up to the body surface.AbstractEnglisch = Multiscale modeling of cardiac electrophysiology helps to better understand the underlying mechanisms of atrial fibrillation, acute cardiac ischemia and pharmacological treatment. For this purpose, measurement data reflecting these conditions have to be integrated into models of cardiac electrophysiology. Several methods for this model adaptation are introduced in this thesis. The resulting effects are investigated in multiscale simulations ranging from the ion channel up to the body surface.
Perspectives on Antiarrhythmic Drug Therapy: Disappointing Past, Current Efforts and Faint Hopes
This eBook is a collection of articles from a Frontiers Research Topic. Frontiers Research Topics are very popular trademarks of the Frontiers Journals Series: they are collections of at least ten articles, all centered on a particular subject. With their unique mix of varied contributions from Original Research to Review Articles, Frontiers Research Topics unify the most influential researchers, the latest key findings and historical advances in a hot research area! Find out more on how to host your own Frontiers Research Topic or contribute to one as an author by contacting the Frontiers Editorial Office: frontiersin.org/about/contact.
Statistical Atlases and Computational Models of the Heart. Multi-Disease, Multi-View, and Multi-Center Right Ventricular Segmentation in Cardiac MRI Challenge
This book constitutes the proceedings of the 12th International Workshop on Statistical Atlases and Computational Models of the Heart, STACOM 2021, as well as the M&Ms-2 Challenge: Multi-Disease, Multi-View and Multi-Center Right Ventricular Segmentation in Cardiac MRI Challenge. The 25 regular workshop papers included in this volume were carefully reviewed and selected after being revised. They deal with cardiac imaging and image processing, machine learning applied to cardiac imaging and image analysis, atlas construction, artificial intelligence, statistical modelling of cardiac function across different patient populations, cardiac computational physiology, model customization, atlas bas...
Safety Pharmacology - Risk Assessment QT Interval Prolongation and Beyond
Current regulatory guidelines for cardiac safety utilize hERG block and QT interval prolongation as risk markers. This strategy has been successful at preventing harmful drugs from being marketed, but criticized for leading to early withdrawal of potentially safe drugs. Here we collected a series of articles presenting new technological and conceptual advances, including refinement of ex vivo and in vitro assays, screens and models, and in silico approaches reflecting the increasing effort that has been put forward by regulatory agencies, industry, and academia to try and address the need of a more accurate, mechanistically-based paradigm of proarrhythmic potential of drugs. This Research Topic is dedicated to the memory of Dr. J. Jeremy Rice, our wonderful friend and colleague.
Functional Imaging and Modeling of the Heart
This book constitutes the refereed proceedings of the 12th International Conference on Functional Imaging and Modeling of the Heart, held in Lyon, France, in June 2023. The 72 full papers were carefully reviewed and selected from 80 submissions. The focus of the papers is on following topics: increased imaging resolutions, data explosion, sophistication of computational models and advent of AI frameworks, while new imaging modalities have emerged (e.g. combined PET-MRI, Spectral CT).
ECG Imaging of Ventricular Activity in Clinical Applications
ECG imaging was performed in humans to reconstruct ventricular activation patterns and localize their excitation origins. The precision of the non-invasive reconstructions was evaluated against invasive measurements and found to be in line with the state-of-the-art literature. Statistics were produced for various excitation origins and reveal the beat-to-beat robustness of the imaging method.
