Machine learning-based prediction of hemodynamic parameters in left coronary artery bifurcation: A CFD approach
Coronary artery disease (CAD) is a leading cause of global mortality, often involving the development of atherosclerotic plaques in coronary arteries, particularly at bifurcation sites. Percutaneous coronary intervention (PCI) of bifurcation lesions presents challenges, necessitating accurate assess...
Saved in:
Main Authors: | Sara Malek, Arshia Eskandari, Mahkame Sharbatdar |
---|---|
Format: | Article |
Language: | English |
Published: |
Elsevier
2025-01-01
|
Series: | Heliyon |
Online Access: | http://www.sciencedirect.com/science/article/pii/S2405844025003536 |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
Diffuseness of coronary artery disease impacts on immediate hemodynamic and predicted clinical outcomes
by: Shigetaka Kageyama, et al.
Published: (2025-01-01) -
The Relationship between Left Ventricular Diastolic Function Parameters and Coronary Artery Disease Severity
by: Khadije Mohammadi, et al.
Published: (2024-12-01) -
A Hemodynamic-Based Evaluation of Applying Different Types of Coronary Artery Bypass Grafts to Coronary Artery Aneurysms
by: Haoran Wang, et al.
Published: (2020-01-01) -
Left Main Coronary Artery Hypoplasia in Elderly
by: Selma Kenar Tiryakioglu, et al.
Published: (2016-01-01) -
Successful Percutaneous Coronary Intervention Using Intravascular Ultrasound-Guided Rewiring Technique in a Case of Spontaneous Coronary Artery Dissection Involving Left Main Bifurcation
by: Yohei Numasawa, et al.
Published: (2020-01-01)