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Discrete Bayesian Network Interpretation of the Cox's Proportional Hazard Model

Kraisangka, Jidapa and Druzdzel, Marek J. (2014) Discrete Bayesian Network Interpretation of the Cox's Proportional Hazard Model. In: Probabilistic Graphical Models. Springer Lecture Notes in Computer Science, 8754 . Springer International Publishing, Heidelberg, 190 - 205. ISBN UNSPECIFIED

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Abstract

Cox’s Proportional Hazards (CPH) model is quite likely the most popular modeling technique in survival analysis. While the CPH model is able to represent relationships between a collection of risks and their common effect, Bayesian networks have become an attractive alter-native with far broader applications. Our paper focuses on a Bayesian network interpretation of the CPH model. We provide a method of en-coding knowledge from existing CPH models in the process of knowledge engineering for Bayesian networks. We compare the accuracy of the resulting Bayesian network to the CPH model, Kaplan-Meier estimate, and Bayesian network learned from data using the EM algorithm. Bayesian networks constructed from CPH model lead to much higher accuracy than other approaches, especially when the number of data records is very small.


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Details

Item Type: Book Section
Status: Published
Creators/Authors:
CreatorsEmailPitt UsernameORCID
Kraisangka, Jidapa
Druzdzel, Marek J.druzdzel@pitt.eduDRUZDZEL
Date: 2014
Date Type: Publication
Series Name: Springer Lecture Notes in Computer Science
Volume: 8754
Publisher: Springer International Publishing
Place of Publication: Heidelberg
Page Range: 190 - 205
DOI or Unique Handle: 10.1007/978-3-319-11433-0_16
Schools and Programs: School of Information Sciences > Information Science
Refereed: Yes
Title of Book: Probabilistic Graphical Models
Editors:
EditorsEmailPitt UsernameORCID
van der Gaag, Linda C.UNSPECIFIEDUNSPECIFIEDUNSPECIFIED
Feelders, Ad J.UNSPECIFIEDUNSPECIFIEDUNSPECIFIED
Official URL: http://link.springer.com/chapter/10.1007/978-3-319...
Date Deposited: 02 Jul 2015 14:34
Last Modified: 01 Nov 2017 12:58
URI: http://d-scholarship.pitt.edu/id/eprint/25525

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