Bayesian calibration of a stochastic, multiscale agent-based model for predicting in vitro tumor growth.

Bayesian calibration of a stochastic, multiscale agent-based model for predicting in vitro tumor growth.

Hybrid multiscale agent-based models (ABMs) are unique in their ability to simulate individual cell interactions and microenvironmental dynamics. Unfortunately, the high computational cost of modeling individual cells, the inherent stochasticity of cell dynamics, and numerous model parameters are fu...

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Bibliographic Details
Main Authors: Ernesto A B F Lima, Danial Faghihi, Russell Philley, Jianchen Yang, John Virostko, Caleb M Phillips, Thomas E Yankeelov
Format: Article
Language:English
Published: Public Library of Science (PLoS) 2021-11-01
Series:PLoS Computational Biology
Online Access:https://doi.org/10.1371/journal.pcbi.1008845

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