Cargando…
Prediction of Left Ventricular Mechanics Using Machine Learning
The goal of this paper was to provide a real-time left ventricular (LV) mechanics simulator using machine learning (ML). Finite element (FE) simulations were conducted for the LV with different material properties to obtain a training set. A hyperelastic fiber-reinforced material model was used to d...
Autores principales: | Dabiri, Yaghoub, Van der Velden, Alex, Sack, Kevin L., Choy, Jenny S., Kassab, Ghassan S., Guccione, Julius M. |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
2019
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6941671/ https://www.ncbi.nlm.nih.gov/pubmed/31903394 http://dx.doi.org/10.3389/fphy.2019.00117 |
Ejemplares similares
-
Application of feed forward and recurrent neural networks in simulation of left ventricular mechanics
por: Dabiri, Yaghoub, et al.
Publicado: (2020) -
Machine learning used for simulation of MitraClip intervention: A proof-of-concept study
por: Dabiri, Yaghoub, et al.
Publicado: (2023) -
Relationship of Transmural Variations in Myofiber Contractility to Left Ventricular Ejection Fraction: Implications for Modeling Heart Failure Phenotype With Preserved Ejection Fraction
por: Dabiri, Yaghoub, et al.
Publicado: (2018) -
Numerical Simulations of MitraClip Placement: Clinical Implications
por: Kamakoti, Ramji, et al.
Publicado: (2019) -
Mitral Valve Atlas for Artificial Intelligence Predictions of MitraClip Intervention Outcomes
por: Dabiri, Yaghoub, et al.
Publicado: (2021)