Diabetes Prediction using Improved Artificial Neural Network using Multilayer Perceptron

International Journal of Electrical and Electronics Engineering

© 2022 by SSRG - IJEEE Journal

Volume 9 Issue 12

Year of Publication : 2022

Authors : T. Madhubala, R. Umagandhi, P. Sathiamurthi

10.14445/23488379/IJEEE-V9I12P115

How to Cite?

T. Madhubala, R. Umagandhi, P. Sathiamurthi, "Diabetes Prediction using Improved Artificial Neural Network using Multilayer Perceptron," SSRG International Journal of Electrical and Electronics Engineering, vol. 9,  no. 12, pp. 167-179, 2022. Crossref, https://doi.org/10.14445/23488379/IJEEE-V9I12P115

Abstract:

Diabetes is a continual health situation that involves how your corpse revolves foodstuff into power. Our body severs most of the food we eat into glucose and discharges it into our bloodstream. When our blood sugar goes up, it signs our pancreas to liberate the insulin. Insulin takes steps to permit the blood glucose into our body’s cells for use as liveliness. If the patient has diabetes, the body cannot produce sufficient insulin. Unmanaged diabetes comes due to hunger, less-healing wounds, frequent urination, more thirst, fatigue, itchy skin, dry and blurry revelation, etc. Hence detection of diabetes is a very virtual role in our country and abroad. The proposed system is Improved Artificial Neutral Network (IANN), which used Pima Indian Diabetes (PID) dataset to construct the deep network. Also, this research used the Weka tool to find the existing classifier performance and proposed IANN outperforms compared to other algorithms

Keywords:

Data Mining, Machine Learning, Artificial Neural Network, Diabetics and Multilayer Perceptron.

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