Machine Learning for Cardiovascular Biomechanics Modeling: Challenges and Beyond
Author:
Funder
National Science Foundation
American Heart Association
Publisher
Springer Science and Business Media LLC
Subject
Biomedical Engineering
Link
https://link.springer.com/content/pdf/10.1007/s10439-022-02967-4.pdf
Reference133 articles.
1. Aggarwal, C. C. Neural Networks and Deep Learning: A Textbook. New York: Springer, 2018.
2. Alber, M., A. B. Tepole, W. R. Cannon, S. De, S. Dura-Bernal, K. Garikipati, G. Karniadakis, W. W. Lytton, P. Perdikaris, L. Petzold, and E. Kuhl. Integrating machine learning and multiscale modeling-perspectives, challenges, and opportunities in the biological, biomedical, and behavioral sciences. NPJ Digital Med. 2(1): 1–11, 2019.
3. Antiga, L., and D. A. Steinman. Rethinking turbulence in blood. Biorheology 46(2):77–81, 2009.
4. Arzani, A. Accounting for residence-time in blood rheology models: do we really need non-Newtonian blood flow modelling in large arteries? J. R. Soc. Interface 15(146):20180486, 2018.
5. Arzani, A., and S. Dawson. Data-driven cardiovascular flow modelling: examples and opportunities. J. R. Soc. Interface 18:20200802, 2021.
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