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AUTHOR(S): Temitayo Oyegoke, Adekemi Amoo, Jeremiah Balogun, Tolulope Alo, Peter Idowu
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TITLE A Predictive Model for the Risk of Infertility in Men using Fuzzy Logic |
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ABSTRACT Infertility in women has been the general trend because people do not believe that men too can be infertile, but nowadays it is has been verified that male as a role to play in infertility as well as the female. This study developed a fuzzy logic model for the prediction of risk of infertility in men. The work identified the non-invasive risk factors and their associated relationship with the risk of male infertility from medical experts; and collected relevant data from 28 males. The model using was formulated using triangular membership functions equal to the number of risk factor labels and adopted the relationship for creating 4374 IF-THEN rules. The model was simulated using Fuzzy Logic Toolbox of the MATLAB software and was validated using the 28 male records collected. The result of the model showed an accuracy of 100% owing to the capacity to map underlying rules to every data record applied. The study concluded that the model will provide effective decision-support required for mitigating the related effects of male infertility in Nigeria. |
KEYWORDS prediction model, infertility in men, fuzzy logic |
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Cite this paper Temitayo Oyegoke, Adekemi Amoo, Jeremiah Balogun, Tolulope Alo, Peter Idowu. (2019) A Predictive Model for the Risk of Infertility in Men using Fuzzy Logic. International Journal of Computers, 4, 27-37 |
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