Applicability of Data Mining Technique Using Bayesians Network in Diagnosis of Genetic Diseases

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Applicability of Data Mining Technique Using Bayesians Network in Diagnosis of Genetic Diseases

Journal Title: International Journal of Advanced Computer Science & Applications - Year 2013, Vol 4, Issue 1

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.

Authors and Affiliations

Hugo Pereira Leite Filho

Keywords

Turner Syndrome probabilistic networks classification techniques based in decision trees

EP ID EP98390
DOI 10.14569/IJACSA.2013.040107
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