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Publication Details
AFRICAN RESEARCH NEXUS
SHINING A SPOTLIGHT ON AFRICAN RESEARCH
mathematics
Analysis of breast cancer profiles using bayesian network modeling
International Journal of Biomathematics, Volume 6, No. 3, Article 1350014, Year 2013
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Description
Breast cancer is the leading cause of cancer-related death for women in Tunisia and the prognosis of its metastasis remains a major problem for oncologists despite advances in treatment. In this work we use Bayesian networks to develop a decision support system that is based on the modeling of relationships between key signaling proteins and clinical and pathological characteristics of breast tumors and patients. Motivated by the lack of prior information on the parameters of the problem, we use the Implicit inference for the structure and parameter learning. A dataset of 84 Tunisian breast cancer patients was used and new prognosis factors were identified. The system predicts a metastasis risk for different patients by computing a score that is the joint probability of the Bayesian network using parameters estimated on the learning database. Based on the results of the developed system we identified that overexpression of ErbB2, ErbB3, bcl2 as well as of oestrogen and progesterone receptors associated with a low level of ErbB4 was the predominant profile associated with high risk of metastasis. © 2013 World Scientific Publishing Company.
Authors & Co-Authors
Ben Hassen, Hanen
Tunisia, Sfax
Centre de Biotechnologie de Sfax
Kallel-Bayoudh, Imen
Tunisia, Sfax
Centre de Biotechnologie de Sfax
Bouchaala, Lobna
Tunisia, Sfax
Centre de Biotechnologie de Sfax
REBAI, AHMED
Tunisia, Sfax
Centre de Biotechnologie de Sfax
Statistics
Citations: 6
Authors: 4
Affiliations: 1
Identifiers
Doi:
10.1142/S1793524513500149
ISSN:
17935245
e-ISSN:
17937159
Research Areas
Cancer
Study Locations
Tunisia
Participants Gender
Female