Exploring Atrial Fibrillation Through Computational Models: Clinical Applications, Mechanisms, and Advancements in Tools
Atrial fibrillation (AF) is the most common cardiac arrhythmia, characterized by a fast and irregular heart rate.Computer modelling has been playing an ever more important role in understanding AF.This review showcases research from the past two years from a variety of aspects relevant to computational modelling of AF.Beginning with research that is directly relevant in clinical settings, such as antiarrhythmic drugs, ablation techniques and blood clot modelling.This is followed by studies that aim to understand the underlying mechanisms behind AF, including influence from fibrosis, fatty tissue, and atrial model size and makeup.The last section features literature on techniques, methodologies and tools that are relevant to AF modelling, such as diffusion algorithms, imaging, and artificial intelligence.
Authors
- James J. Kennelly (ORCID: https://orcid.org/0000-0002-7631-5426)
- Jichao Zhao (ORCID: https://orcid.org/0000-0003-3303-0401)
- Roshan Sharma
Institutions
- Auckland Institute of Studies (NZ)
- University of Auckland (NZ)
- Auckland University of Technology (NZ)
Publication Details
- Journal
- Computing in cardiology
- Published
- 2024-12-01
- DOI
- https://doi.org/10.22489/cinc.2024.133
- Primary Topic
- Atrial Fibrillation Management and Outcomes
- Type
- article
- Field-Weighted Citation Impact
- 0.00