ML Anthology

Dynamic Bayesian Network Modeling of Vascularization in Engineered Tissues

Caner Komurlu, Jinjian Shao, Mustafa Bilgic
UAI 2014 pp. 89-98
/uai/2014/komurlu2014uai-dynamic/

Abstract

In this paper, we present a dynamic Bayesian network (DBN) approach to modeling vascu-larization in engineered tissues. Injuries and diseases can cause significant tissue loss to the degree where the body is unable to heal itself. Tissue engineering aims to replace the lost tissue through use of stem cells and bio-materials. For tissue cells to multiply and migrate, they need to be close to blood ves-sels, and hence proper vascularization of the tissue is an essential component of the en-gineering process. We model vascularization through a DBN whose structure and parame-ters are elicited from experts. The DBN pro-vides spatial and temporal probabilistic rea-soning, enabling tissue engineers to test sen-sitivity of vascularization to various factors and gain useful insights into the vasculariza-tion process. We present initial results in this paper and then discuss a number of future re-search problems and challenges. 1

PDF UAI Semantic Scholar

Cite

Text

Komurlu et al. "Dynamic Bayesian Network Modeling of Vascularization in Engineered Tissues." Conference on Uncertainty in Artificial Intelligence, 2014.

Markdown

[Komurlu et al. "Dynamic Bayesian Network Modeling of Vascularization in Engineered Tissues." Conference on Uncertainty in Artificial Intelligence, 2014.](https://mlanthology.org/uai/2014/komurlu2014uai-dynamic/)

BibTeX

@inproceedings{komurlu2014uai-dynamic,
  title     = {{Dynamic Bayesian Network Modeling of Vascularization in Engineered Tissues}},
  author    = {Komurlu, Caner and Shao, Jinjian and Bilgic, Mustafa},
  booktitle = {Conference on Uncertainty in Artificial Intelligence},
  year      = {2014},
  pages     = {89-98},
  url       = {https://mlanthology.org/uai/2014/komurlu2014uai-dynamic/}
}