Fast Posterior Estimation of Cardiac Electrophysiological Model Parameters via Bayesian Active Learning

Probabilistic estimation of cardiac electrophysiological model parameters serves an important step toward model personalization and uncertain quantification. The expensive computation associated with these model simulations, however, makes direct Markov Chain Monte Carlo (MCMC) sampling of the poste...

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Detalles Bibliográficos
Autores principales: Zaman, Md Shakil, Dhamala, Jwala, Bajracharya, Pradeep, Sapp, John L., Horácek, B. Milan, Wu, Katherine C., Trayanova, Natalia A., Wang, Linwei
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2021
Materias:
Physiology
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8573318/
https://www.ncbi.nlm.nih.gov/pubmed/34759835
http://dx.doi.org/10.3389/fphys.2021.740306

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8573318/
https://www.ncbi.nlm.nih.gov/pubmed/34759835
http://dx.doi.org/10.3389/fphys.2021.740306

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