Socioeconomic and Age-incidence of Breast Cancer: Modeling Using Artificial Intelligence Technique
Khaoula Bouharati, Mokhtar Hamdi-Cherif, Abas Mahnane, Slimane Laaouamri, Souad Bouaoud, Hafida Boukharouba, Oussama Bouharati, Nassim Boucenna, Saddek Bouharati
Journal of Cancer and Tumor International · pp. 1–8 · Published 14 Mar 2016
10.9734/JCTI/2016/24774Abstract
Purpose: The majority of women presenting with breast cancer it are not possible to identify specific risk factors. Age is the major factor on breast cancer incidence. Also, poverty status can be classified. Because of the weakness of the underlying empirical data in many countries, a number of the indicators presented here are associated with significant uncertainty. The fuzzy logic inference method as an artificial intelligence technique is proposed for modeling data. Methods: In our situation it is very difficult to use classical logic to model a system with the available knowledge. Classical logic does not allow working with uncertainty in the information when knowledge about the behavior of the systems is imprecise. A fuzzy system was constructed with three inputs parameters and one output expressing the number of cases. Results: The result of the fuzzy program so far, is a numeric and symbolic terms of number of breast cancer recorded; using the fuzzy inputs data in the universe of discourse (poor, near poor or non-poor), age and period. Conclusion: Once the established system, it allows to predict the impact of each input and its effect on the output parameter. Assessing the degree of impact allows us to define the set the factor that has the greatest impact in the fight against breast cancer. The result is the contribution of the set of input variable, taking into account inaccuracies and the complexity involved in the process.
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