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Application of Dynamic Bayesian Networks to cervical cancer screening

Onisko, Agnieszka and Druzdzel, Marek J. and Austin, R. Marshall (2009) Application of Dynamic Bayesian Networks to cervical cancer screening. In: Proceedings on XI International Conference on Artificial Intelligence: Al-24’2009, June 2009 - June 2009, Krakow, Poland.

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Abstract

Dynamic Bayesian networks (DBNs) offer a framework for explicit modeling of temporal relationships. They are often used as prognostic tools. In medicine, for example, they can assist planning treatment options or clinical management of patients. They have been also widely applied to genomics and proteomics. This paper describes the Pittsburgh Cervical Cancer Screening Model (PCCSM), a DBN that combines two sources of knowledge: expert opinion and objective hospital data. The model serves as a convenient tool for assessing the risk of cervical precancer and invasive cervical cancer over time. These quantitative risk assessments are helpful for establishing the optimal timing of follow-up screening and are the first step toward generating individualized reevaluation scheduling.


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Details

Item Type: Conference or Workshop Item (Paper)
Status: Published
Creators/Authors:
CreatorsEmailPitt UsernameORCID
Onisko, Agnieszka
Druzdzel, Marek J.marek@sis.pitt.eduDRUZDZEL0000-0002-7598-2286
Austin, R. Marshall
Date: 2009
Date Type: Publication
Publisher: Publishing House of the University of Podlasie
Place of Publication: Siedlce, Poland
Page Range: 5 - 14
Event Title: Proceedings on XI International Conference on Artificial Intelligence: Al-24’2009
Event Dates: June 2009 - June 2009
Event Type: Conference
Institution: University of Pittsburgh
Schools and Programs: School of Information Sciences > Information Science
Refereed: Yes
Date Deposited: 12 Jul 2011 14:03
Last Modified: 05 Mar 2019 01:55
URI: http://d-scholarship.pitt.edu/id/eprint/6012

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