Multi-scale modeling of cardiac arrhythmias
Abstract/Contents
- Abstract
- In the United States, almost half a million people die each year as a result of cardiac arrhythmias. These diseases comprise a number of abnormal rhythms, where the electrical activity of the heart is disturbed. Despite decades of research, the mechanisms by which arrhythmias develop remain poorly explained. One of the main challenges is that even though arrhythmias appear at the organ level, they can be triggered by sub-cellular changes, creating an inherently multi-scale problem. Computational models can bridge across scales to provide mechanistic understanding of these conditions. This thesis elaborates on the development of these models and their applicability to different types of arrhythmias. We study how different components of these models affect their response and the consequences of clinical applications. Moreover, we develop a high resolution, multi-scale model of the heart. We model from the ionic channels in the cell, to the different distributions of cell populations, to the entire heart. This tool allow us to study, for example, the development of drug-induced arrhythmias, where if specific ionic channels are blocked, arrhythmias appear spontaneously. We also apply machine learning techniques to extract knowledge and alleviate the computational cost of these high resolution models. We anticipate the newly developed models and methodologies will help to elaborate mechanistic explanations of the development of arrhythmias and elucidate new treatments.
Description
| Type of resource | text |
|---|---|
| Form | electronic resource; remote; computer; online resource |
| Extent | 1 online resource. |
| Place | California |
| Place | [Stanford, California] |
| Publisher | [Stanford University] |
| Copyright date | 2018; ©2018 |
| Publication date | 2018; 2019 |
| Issuance | monographic |
| Language | English |
Creators/Contributors
| Author | Sahli, Francisco |
|---|---|
| Degree supervisor | Kuhl, Ellen, 1971- |
| Thesis advisor | Kuhl, Ellen, 1971- |
| Thesis advisor | Narayan, Sanjiv M |
| Thesis advisor | Pinsky, P |
| Degree committee member | Narayan, Sanjiv M |
| Degree committee member | Pinsky, P |
| Associated with | Stanford University, Department of Mechanical Engineering. |
Subjects
| Genre | Theses |
|---|---|
| Genre | Text |
Bibliographic information
| Statement of responsibility | Francisco Sahli Costabal. |
|---|---|
| Note | Submitted to the Department of Mechanical Engineering. |
| Thesis | Thesis Ph.D. Stanford University 2019. |
| Location | electronic resource |
Access conditions
- Copyright
- © 2018 by Francisco Sahli
- License
- This work is licensed under a Creative Commons Attribution Non Commercial No Derivatives 3.0 Unported license (CC BY-NC-ND).
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