%0 Journal Article %1 IJACSA.2013.040107 %A Filho, Hugo Pereira Leite %D 2013 %J International Journal of Advanced Computer Science and Applications(IJACSA) %K Syndrome; Turner based classification decision in networks; probabilistic techniques trees %N 1 %T Applicability of Data Mining Technique Using Bayesians Network in Diagnosis of Genetic Diseases %U http://ijacsa.thesai.org/ %V 4 %X 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 (Na&\#239;ve 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 Na&\#239;ve 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 Na&\#239;ve Bayes. However, the neural network did not promote a satisfactory solution.

@article{IJACSA.2013.040107, 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 (Na\&\#239;ve 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 Na\&\#239;ve 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 Na\&\#239;ve Bayes. However, the neural network did not promote a satisfactory solution.}, added-at = {2014-02-21T08:00:08.000+0100}, author = {Filho, Hugo Pereira Leite}, biburl = {https://www.bibsonomy.org/bibtex/2abcfb55b78a3d0249637f5b2da3ae455/thesaiorg}, interhash = {0117f22f1aff334f3136ac316e4156fe}, intrahash = {abcfb55b78a3d0249637f5b2da3ae455}, journal = {International Journal of Advanced Computer Science and Applications(IJACSA)}, keywords = {Syndrome; Turner based classification decision in networks; probabilistic techniques trees}, number = 1, timestamp = {2014-02-21T08:00:08.000+0100}, title = {{Applicability of Data Mining Technique Using Bayesians Network in Diagnosis of Genetic Diseases}}, url = {http://ijacsa.thesai.org/}, volume = 4, year = 2013 }