Diabetes Prediction Using Artificial Neural Network

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Abstract
Diabetes is one of the most common diseases worldwide where a cure is not found for it yet. Annually it cost a lot of money to care for people with diabetes. Thus the most important issue is the prediction to be very accurate and to use a reliable method for that. One of these methods is using artificial intelligence systems and in particular is the use of Artificial Neural Networks (ANN). So in this paper, we used artificial neural networks to predict whether a person is diabetic or not. The criterion was to minimize the error function in neural network training using a neural network model. After training the ANN model, the average error function of the neural network was equal to 0.01 and the accuracy of the prediction of whether a person is diabetics or not was 87.3%
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EL_DPU-5
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First archival date: 2019-02-09
Latest version: 2 (2019-02-19)
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References found in this work BETA
Detecting Health Problems Related to Addiction of Video Game Playing Using an Expert System.Samy S. Abu Naser & Mohran H. Al-Bayed - 2016 - World Wide Journal of Multidisciplinary Research and Development 2 (9):7-12.
A Proposed Knowledge Based System for Desktop PC Troubleshooting.Ahmed Wahib Dahouk & Samy S. Abu-Naser - 2018 - International Journal of Academic Pedagogical Research (IJAPR) 2 (6):1-8.
Proposed Expert System for Calculating Inheritance in Islam.Alaa N. Akkila & Samy S. Abu Naser - 2016 - World Wide Journal of Multidisciplinary Research and Development 2 (9):38-48.
Rule Based System for Diagnosing Wireless Connection Problems Using SL5 Object.Samy S. Abu Naser, Wadee W. Alamawi & Mostafa F. Alfarra - 2016 - International Journal of Information Technology and Electrical Engineering 5 (6):26-33.

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Citations of this work BETA
Image-Based Tomato Leaves Diseases Detection Using Deep Learning.Belal A. M. Ashqar & Samy S. Abu-Naser - 2019 - International Journal of Academic Engineering Research (IJAER) 2 (12):10-16.

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