Safial Islam Ayon

Work place: Department of Computer Science and Engineering, Khulna University of Engineering & Technology, Khulna-9203, Bangladesh



Research Interests: Computer systems and computational processes, Computational Learning Theory, Swarm Intelligence, Embedded System, Systems Architecture, Network Architecture


Safial Islam Ayon is a B.Sc. student in the Computer Science and Engineering (CSE) department at the Khulna University of Engineering and Technology (KUET), Khulna, Bangladesh. Currently, he is the final year student. His research interests focus on deep neural network, machine learning, embedded systems, and swarm intelligence.

Author Articles
Diabetes Prediction: A Deep Learning Approach

By Safial Islam Ayon

DOI:, Pub. Date: 8 Mar. 2019

Nowadays, Diabetes is one of the most common and severe diseases in Bangladesh as well as all over the world. It is not only harmful to the blood but also causes different kinds of diseases like blindness, renal disease, kidney problem, heart diseases etc. that causes a lot of death per year. So, it badly needs to develop a system that can effectively diagnose the diabetes patients using medical details. We propose a strategy for the diagnosis of diabetes using deep neural network by training its attributes in five and ten-fold cross-validation fashion. The Pima Indian Diabetes (PID) data set is retrieved from the UCI machine learning repository database. The results on PID dataset demonstrate that deep learning approach design an auspicious system for the prediction of diabetes with prediction accuracy of 98.35%, F1 score of 98, and MCC of 97 for five-fold cross-validation. Additionally, accuracy of 97.11%, sensitivity of 96.25%, and specificity of 98.80% are obtained for ten-fold cross-validation. The experimental results exhibit that the proposed system provides promising results in case of five-fold cross-validation.

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