Applicability of Data Mining Technique Using Bayesians Network in Diagnosis of Genetic Diseases
H. Filho. International Journal of Advanced Computer Science and Applications(IJACSA), (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 (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.
%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
}