Asilian Bidgoli A (PhD), Ebrahimpour-Komleh H (PhD), Mousavirad SJ* (PhD)
Department of Computer Engineering, University of Kashan, Kashan, Iran
Received: 23 Jan 2016, Accepted: 3 May 2016
Introduction: Infertility is one of the most important problems, especially among males which has received special attention recently. Male infertility can be affected by different factors. There is now a large body of evidence to support the effects of life styles and environmental factors on semen quality. Data mining methods in artificial intelligence, as a decision support system, could be helpful in medical diagnosis of male infertility.
Methods: The influencing factors of seminal quality, and as a result ability to detect the infertility in males was assessed in this study using data mining algorithms in artificial intelligence. The dataset of 100 volunteers among students of University of Alicante were used. After data balancing different classifiers such as neural network were used to find the best classifier to predict the male infertility.
Results: The proposed algorithm is evaluated with different data mining algorithms to find a better analytical application of the algorithm. Support vector machine had the best accuracy (%95.15) to predict proposed infertility in male compared to the other classifiers. The proposed algorithm has a competitive accuracy compared to other algorithms.
Conclusion: The proposed algorithm is able to predict male infertility from lifestyle and environmental factors using data mining algorithms.
Key words: Male Infertility, Artificial intelligence, Data mining algorithms, Support vector machine, Support decision system
Please cite this article as follows:
Asilian Bidgoli A, Ebrahimpour-Komleh H, Mousavirad SJ. Male Infertility Prediction from Environmental Factors and Lifestyle Using Artificial Intelligence Algorithms. Hakim Health Sys Res 2016; 19(2): 72- 80.
*Corresponding Author: Department of Computer Engineering, University of Kashan, Kashan, Iran.
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