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...
Enregistré dans:
Auteurs principaux: | Yaghoub Dabiri, Alex Van der Velden, Kevin L. Sack, Jenny S. Choy, Julius M. Guccione, Ghassan S. Kassab |
---|---|
Format: | article |
Langue: | EN |
Publié: |
Nature Portfolio
2020
|
Sujets: | |
Accès en ligne: | https://doaj.org/article/d1e753bc8d8d4b1686bf77a7c7d2985d |
Tags: |
Ajouter un tag
Pas de tags, Soyez le premier à ajouter un tag!
|
Documents similaires
-
Transmural Distribution of Coronary Perfusion and Myocardial Work Density Due to Alterations in Ventricular Loading, Geometry and Contractility
par: Lei Fan, et autres
Publié: (2021) -
Effects of Cannabis on Cardiovascular System: The Good, the Bad, and the Many Unknowns
par: Ali E. Dabiri, et autres
Publié: (2021) -
Electrical Load Demand Forecasting Using Feed-Forward Neural Networks
par: Eduardo Machado, et autres
Publié: (2021) -
Ensemble Feed-Forward Neural Network and Support Vector Machine for Prediction of Multiclass Malaria Infection
par: Opeyemi Aderiike Abisoye, et autres
Publié: (2021) -
Left ventricular noncompaction cardiomyopathy
par: Amer Hawatmeh, et autres
Publié: (2017)