Abstract
A hybrid model, combining Bayesian network and a multicriteria method, is presented in order to assist with the decision making process about which questions would be more attractive to the definition of the diagnosis of Diabetes type 2. We have proposed the application of an expert system structured in probability rules and structured representations of knowledge in production rules and probabilities (Artificial Intelligence - AI). The importance of the early diagnosis associated with the appropriate treatment is to decrease the chance of developing the complications of diabetes, reducing the impact on our society. Diabetes is a group of metabolic diseases characterized by hyperglycemia resulting from defects in insulin secretion, insulin action, or both.
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Menezes, A.C., Pinheiro, P.R., Pinheiro, M.C.D., Cavalcante, T.P. (2012). Towards the Applied Hybrid Model in Decision Making: Support the Early Diagnosis of Type 2 Diabetes. In: Liu, B., Ma, M., Chang, J. (eds) Information Computing and Applications. ICICA 2012. Lecture Notes in Computer Science, vol 7473. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-34062-8_84
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DOI: https://doi.org/10.1007/978-3-642-34062-8_84
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