ECG-Based Unsupervised Clustering in Coronary Artery Disease Associates with Ventricular Arrhythmia
DOI:
https://doi.org/10.26754/jjii3a.20239034Abstract
Coronary Artery Disease (CAD) is a leading cause of life-threatening ventricular arrhythmias (LTVAs). This study aimed to identify distinct clusters of CAD individuals based on QRS morphology using a 3-nearest neighbors clustering algorithm. Cluster 1, characterized by the lowest QRS amplitudes and widest QRS complexes, was strongly associated with LTVA risk.
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Published
2023-07-07
How to Cite
Madrid, J., Ramírez, J., & Mincholé, A. (2023). ECG-Based Unsupervised Clustering in Coronary Artery Disease Associates with Ventricular Arrhythmia. Jornada De Jóvenes Investigadores Del I3A, 11. https://doi.org/10.26754/jjii3a.20239034
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Section
Artículos (Ingeniería Biomédica)
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Copyright (c) 2023 Josseline Madrid, Julia Ramírez, Ana Mincholé
This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.