Design of a deep neural network for diabetes prediction


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Authors

  • FERAS KHALEL Dept. of Computer Engineering, Karabuk University, Demir Celik Campus, 78050 Karabuk/Turkey
  • NEHAD T.A RAMAHA Dept. of Computer Engineering, Karabuk University, Demir Celik Campus, 78050 Karabuk/Turkey

Keywords:

Diabetes, Pima Dataset, Neural Network, Deep Learning, Machine Learning

Abstract

Diabetes is a chronic disease with many complications that follow the disease and is one of the causes of death worldwide. The number of people infected with this disease is increasing every day. Therefore, predicting this disease at an early stage helps to avoid many complications that follow the disease. Therefore, many medical sectors have begun to take an interest in using artificial intelligence technologies and benefiting from their services. Data mining and machine learning techniques are used to predict the patient's condition at an early stage. Therefore, this paper uses a neural network containing more than one hidden layer for disease prediction. The designed network gave an accuracy of 95.40%. The accuracy of the Recall scale for infected patients reached 96.59%. It is better than the result of previous studies mentioned in this paper.c

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Published

2023-03-18

How to Cite

KHALEL , F., & RAMAHA, N. T. (2023). Design of a deep neural network for diabetes prediction. International Conference on Scientific and Academic Research, 1, 278–282. Retrieved from https://as-proceeding.com/index.php/icsar/article/view/311

Conference Proceedings Volume

Vol. 1 (2023): Proceeding Book of 2nd International Conference on Scientific and Academic Research ICSAR 2023

Section

Conference Papers