Comparative Analysis of Predictive Models for the Likelihood of Infertility in Women Using Supervised Machine Learning Techniques
Infertility is a worldwide problem, affecting 8% – 15% of the couples in their reproductive age. WHO estimates that there are 60 - 80 million infertile couples worldwide with the highest incidence in some regions of Sub-Saharan Africa also infertility rate may reach 50% compared to 20% in Eastern Mediterranean Region and 11% in the developed world. Infertility has caused considerable social, emotional and psychological stress between couples, among families, within the individual concerned and the society at large. Historical data constituting information describing the risk factors of infertility alongside the respective infertility likelihood status of women was collected from Obafemi Awolowo University Teaching Hospital Complex (OAUTHC). The predictive model was formulated using naïve Bayes’, decision trees and multi-layer perceptron algorithm – supervised machine learning algorithms. The formulated model was simulated using the Waikato Environment for Knowledge Analysis (WEKA) environment. The results of the performance evaluation of the machine learning algorithms showed that the C4.5 decision trees and the multi-layer perceptron with an accuracy of 74.4% each outperformed the naïve Bayes’ algorithm. In addition, the decision trees algorithm recognized variables relevant to predicting infertility and a rule that can be applied on patient risk factor records for infertility likelihood prediction was deduced from the tree structure. This showed how effective machine learning algorithms can be used in predicting the likelihood of infertility in Nigerian women.
A. Abbey, Adjusting to infertility. In Harvey, JD and Miller, ED (Eds.) Loss and Trauma: General and Close Relationship Perspectives, Ann Arbour, MI: Edwards Brothers, 2000.
J. B. L. C. J. N. K. Boivin, "International Estimates of Infertility Prevalence and Treatment Seeking: Potential need and demand for infertility medical," Human Reproduction, vol. 24, pp. 2379-2380, 2009.
W. H. Organization, Infertility: A Tabulation of Available Data on prevalence of Primary and Secondary Infertility. Programme on Maternal and Child Health and Family Planning, Division of Family Health,, Geneva: World Health Organisation, 1999.
A. S. f. Reproductive, " Fertility sterility," ASRM, vol. 90, no. 7, pp. 2361- 2365, 2008.
N. R.-D. M. E. M. K. Skakkebaek, "Testicular dysgenesis syndrome: An increasingly common developmental disorder with environmental aspects," Human Reproduction, vol. 16, p. 972–980, 2001.
E. W. T. Puscheck, "Infertility: e-Medicine Specialties Obstetrics and Gynaecology, .," 2009. [Online]. Available: http://emedicine.medscape.com/article/274143. [Accessed 25 May 2015].
B. M. A. B. M. Audu, "Clinical Presentation of Infertility in Gombe, North-Eastern, Nigeria," Tropical Journal of Obstetrics Gynaecology, vol. 20, pp. 93-96, 2003.
F. Okonofua, "Infertility in Developing Countries," British Journal of Obstetrics and Gynecology, vol. 103, pp. 957-962, 1996.
A. Idrisa, "Infertility," in Comprehensive Gynaecology in the tropics, Accra, Graphic Packaging, 2005, p. 333–345.
W. H. Organization, "Infections, Pregnancies, and Infertility: Perspectives on Prevention. Fertility and Sterility," 1992.
M. K. R. Durairaj, "Data Mining application on IVF Data for the selection of influential parameters on Fertility," International Journal of Engineering and Advanced Technology , vol. 2, no. 6, pp. 262-266, 2006.
R. S. A. M. D. S. I. Saith, "Application of In-situ hybridization techniques to study human pre-implantation embryos: a review.," Journal of human reproductive , vol. 4, no. 2, pp. 121-134, 1998.
S. K. A. K. N. Shen, "Statistical analysis of factors affecting fertilization rates and clinical outcome associated with intracytoplasmic sperm injection," Fertility and Sterility , vol. 79, no. 2, pp. 355-360, 2003.
Copyright (c) 2018 Computer Reviews Journal
This work is licensed under a Creative Commons Attribution 4.0 International License.
Authors retain the copyright of their manuscripts, and all Open Access articles are distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided that the original work is properly cited.
Computer Reviews Journal allow the author(s) to retain publishing rights without restrictions.