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Medical Factors-Based Mobile Application for Choosing Contraceptives: A Data Mining Approach

Women's negative experience with contraception and understanding of the experience differentials, coupled with Limited information accessibility on contraceptives to healthcare centers, is responsible for the unwillingness and discontinuation in the use of contraceptives in Nigeria. The study aims at developing a Medical Factor based Mobile application Model for contraceptive implants using K-Nearest Neighbour (KNN) and Support Vector Machine (SVM) techniques for the prediction of discomfort, and blood type. KNN and SVM techniques in R were the two methods used to develop a model to classify blood group types based on discomfort and vice versa. 10-fold cross-validation was carried out and was repeated 3 times and the optimal values were selected. The model was tested by the use of Predict function in which test data was used as the new data (input data) of the model. Experimental results showed the prediction accuracy of the KNN model was 85.72% and the SVM model was 92.2%. SVM outperformed KNN. However, the performances of models imply that the application can be used by women as the means for accessing information on discomforts associated with contraceptive implants as well as blood type. Most women with similar blood types have similar experiences (discomforts). Therefore this model can be used to choose the right contraceptive that is friendly to one blood type. The prediction mobile application of the tested model frontend was implemented in Android built-in with Java as the programming language. The backend was designed using structural query language in the WAMP server.

Contraceptives, Data Mining, k-NN Algorithm, Support Vector Machine

APA Style

Bala Pwa’anda Bulus, Yusuf Musa Malgwi. (2023). Medical Factors-Based Mobile Application for Choosing Contraceptives: A Data Mining Approach. American Journal of Data Mining and Knowledge Discovery, 8(1), 1-10. https://doi.org/10.11648/j.ajdmkd.20230801.11

ACS Style

Bala Pwa’anda Bulus; Yusuf Musa Malgwi. Medical Factors-Based Mobile Application for Choosing Contraceptives: A Data Mining Approach. Am. J. Data Min. Knowl. Discov. 2023, 8(1), 1-10. doi: 10.11648/j.ajdmkd.20230801.11

AMA Style

Bala Pwa’anda Bulus, Yusuf Musa Malgwi. Medical Factors-Based Mobile Application for Choosing Contraceptives: A Data Mining Approach. Am J Data Min Knowl Discov. 2023;8(1):1-10. doi: 10.11648/j.ajdmkd.20230801.11

Copyright © 2023 Authors retain the copyright of this article.
This article is an open access article distributed under the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/) which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

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