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Activity Number:
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285
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Type:
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Contributed
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Date/Time:
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Tuesday, August 4, 2009 : 8:30 AM to 10:20 AM
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Sponsor:
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Section on Health Policy Statistics
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| Abstract - #304117 |
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Title:
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A Stochastic and State Space Model for Human Eye Cancer Involving Both Hereditary and Non-Hereditary Cancer Genes
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Author(s):
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Hong Zhou*+ and Wai-Yuan Tan
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Companies:
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Arkansas State University and University of Memphis
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Address:
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P.O. Box 2597, Jonesboro, AR, 72467,
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Keywords:
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Stochastic model ; State space model ; Carcinogenesis ; Bayesian ; Eye cancer
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Abstract:
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It is well-documented that the human eye cancer is initiated by the tumor suppressor gene-retinoblastoma (RB) via a two-stage model and that the mutated RB gene can be inherited from parent to children if the germline cell has carried the mutated RB gene (Cavenee et al. 1985; Tan 1991, Chapter 3; Weinberg 2007, Chapter 5). However, it is questionable if the two-stage model is really appropriate (DiCiommo et al. 2000). Based on results from recent biological findings, in this paper we propose a new stochastic and state space model for human eye cancer through cancer incidence data as given by the SEER data set. We develop a generalized Bayesian approach to estimate the unknown genetic parameters and to predict the state variables.
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