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Digital Object Identifier (DOI) : 10.14569/IJACSA.2013.040107
Article Published in International Journal of Advanced Computer Science and Applications(IJACSA), Volume 4 Issue 1, 2013.
Abstract: This study aims to identify a methodology to aid in the identification of diagnosis for chromosomal abnormalities and genetic diseases, presenting as a tutorial model the Turner Syndrome. So, it has been used classification techniques based in decision trees, probabilistic networks (Naïve Bayes, TAN e BAN) and neural MLP network (Multi-Layer Perception) and training algorithm by error retro-propagation. Described tools capable of propagating evidence and developing techniques of generating efficient inference techniques to combine expert knowledge with data defined in a database. We have come to a conclusion about the best solution to work out the show problem in this study that was the Naïve Bayes model, because this presented the greatest accuracy. The decision - ID3, TAN e BAN tree models presented solutions to the indicated problem, but those were not as much satisfactory as the Naïve Bayes. However, the neural network did not promote a satisfactory solution.
Hugo Pereira Leite Filho, “Applicability of Data Mining Technique Using Bayesians Network in Diagnosis of Genetic Diseases ” International Journal of Advanced Computer Science and Applications(IJACSA), 4(1), 2013. http://dx.doi.org/10.14569/IJACSA.2013.040107