Application of multilayer perceptron artificial neural network in the diagnosis of type 2 diabetes
Publish place: The 7th International Conference on Economics and Management
Publish Year: 1395
نوع سند: مقاله کنفرانسی
زبان: English
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ICOEM01_136
تاریخ نمایه سازی: 25 آذر 1395
Abstract:
People use various approaches for accurate diagnosis of the disease that one of the mostimportant methods is artificial neural networks (ANNs). Because to diagnose individuals’ diseasethe methods should be used that have a minimum of errors in diagnosis that ANNs have thischaracteristic. Therefore, this paper discusses the diagnoses of presence or absence of type 2diabetes by using ANN of Multilayer Perceptron (MLP). This paper tries to investigate thepresence or absence of type 2 diabetes using ANN of MLP with back-propagation algorithm. Inthis paper, we implemented ANN of MLP with back-propagation algorithm in MATLABenvironment to diagnose type 2 diabetes with data sets that we have which the performancecriterion is to maximize the accuracy of diagnosis of type 2 diabetes in the process of training andtesting. According to the Pima Indians Diabetes Dataset, the obtained result was that the trainingaccuracy was %0.78 and testing accuracy was %0.81.
Keywords:
Artificial neural networks (ANNs) , Multilayer perceptron (MLP) , Back-propagationalgorithm , Diabetes type 3 , Pima Indians Diabetes Data Set , Accuracy of training , Accuracy oftesting
Authors
Arman Abdollahpour
Department of Computer Engineering, East Azarbaijan Science and Research Branch, Islamic AzadUniversity,Tabriz, Iran- 1Department of Computer Engineering, Tabriz Branch, Islamic Azad University, Tabriz, Iran
Mohammad Amin Karimi
Department of Computer Engineering, Tabriz Branch, Islamic Azad University, Tabriz, Iran
Siamak Ebrahimi
Department of Computer Engineering, Tabriz Branch, Islamic Azad University, Tabriz, Iran