Mathematics and Computer Science
Volume 4, Issue 3, May 2019, Pages: 63-67
Received: Mar. 9, 2019;
Accepted: Apr. 22, 2019;
Published: Oct. 12, 2019
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Auwal Nata’ala, Department of Computer Science, Faculty of Science Federal Polytechnic, Kaura-Namoda, Nigeria
Hamman Dikko Muazu, Department of Operation Research, Faculty of Pure and Applied Science, Modibbo Adama University of Technology, Yola, Nigeria
Ibrahim Goni, Department of Computer Science, Faculty of Science Adamawa State University, Mubi, Nigeria
Abdullahi Mohammed Jingi, Department of Computer Science, Faculty of Science Adamawa State University, Mubi, Nigeria
Diabetes is a chronic disease that occurs when the pancreas does not produce enough insulin. The main aim of this research work was to determine the blood glucose level of diabetic patient using adaptive Neuro-fuzzy. Data of 80 diabetic patients were collected from Federal Medical Centre Jalingo. It was used for training and testing the system, Gaussian Membership function was used, hybrid training algorithm was used for training and testing, the error obtain is 0.0008333 at epoch 4 which shows that the training performance is exactly 99.99% and testing performance of the system are 99.99% at epoch 4. This shows that adaptive Neuro-fuzzy system can be applied to medical diagnosis because of the error obtained.
Hamman Dikko Muazu,
Abdullahi Mohammed Jingi,
Adaptive Neuro-Fuzzy System to Determine the Blood Glucose Level of Diabetic, Mathematics and Computer Science.
Vol. 4, No. 3,
2019, pp. 63-67.
Copyright © 2019 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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