Application of feed forward and recurrent neural networks in simulation of left ventricular mechanics
Abstract An understanding of left ventricle (LV) mechanics is fundamental for designing better preventive, diagnostic, and treatment strategies for improved heart function. Because of the costs of clinical and experimental studies to treat and understand heart function, respectively, in-silico model...
Saved in:
Main Authors: | Yaghoub Dabiri, Alex Van der Velden, Kevin L. Sack, Jenny S. Choy, Julius M. Guccione, Ghassan S. Kassab |
---|---|
Format: | article |
Language: | EN |
Published: |
Nature Portfolio
2020
|
Subjects: | |
Online Access: | https://doaj.org/article/d1e753bc8d8d4b1686bf77a7c7d2985d |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
Transmural Distribution of Coronary Perfusion and Myocardial Work Density Due to Alterations in Ventricular Loading, Geometry and Contractility
by: Lei Fan, et al.
Published: (2021) -
Effects of Cannabis on Cardiovascular System: The Good, the Bad, and the Many Unknowns
by: Ali E. Dabiri, et al.
Published: (2021) -
Electrical Load Demand Forecasting Using Feed-Forward Neural Networks
by: Eduardo Machado, et al.
Published: (2021) -
Ensemble Feed-Forward Neural Network and Support Vector Machine for Prediction of Multiclass Malaria Infection
by: Opeyemi Aderiike Abisoye, et al.
Published: (2021) -
Left ventricular noncompaction cardiomyopathy
by: Amer Hawatmeh, et al.
Published: (2017)