Ebenezer Obaloluwa Olaniyi; Oyebade Kayode Oyedotun; Khashman Adnan

Heart Diseases Diagnosis Using Neural Networks Arbitration

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Author(s)

Ebenezer Obaloluwa Olaniyi ^1,* Oyebade Kayode Oyedotun ¹ Khashman Adnan ²

1. Near East University, Lefkosa, via Mersin 10, Turkey, Department of Electrical/Electronic Engineering, Member Center of Innovation for Artificial Intelligence

2. Founder (and Director), Center of Innovation for Artificial Intelligence British University of Nicosia, Via Mersin 10, Turkey

* Corresponding author.

DOI: https://doi.org/10.5815/ijisa.2015.12.08

Received: 1 May 2015 / Revised: 4 Aug. 2015 / Accepted: 5 Sep. 2015 / Published: 8 Nov. 2015

Index Terms

Diagnosis, Heart disease, Neural network, Support vector machine

Abstract

There is an increase in death rate yearly as a result of heart diseases. One of the major factors that cause this increase is misdiagnoses on the part of medical doctors or ignorance on the part of the patient. Heart diseases can be described as any kind of disorder that affects the heart. In this research work, causes of heart diseases, the complications and the remedies for the diseases have been considered. An intelligent system which can diagnose heart diseases has been implemented. This system will prevent misdiagnosis which is the major error that may occur by medical doctors. The dataset of statlog heart disease has been used to carry out this experiment. The dataset comprises attributes of patients diagnosed for heart diseases. The diagnosis was used to confirm whether heart disease is present or absent in the patient. The datasets were obtained from the UCI Machine Learning. This dataset was divided into training, validation set and testing set, to be fed into the network. The intelligent system was modeled on feed forward multilayer perceptron, and support vector machine. The recognition rate obtained from these models were later compared to ascertain the best model for the intelligent system due to its significance in medical field. The results obtained are 85%, 87.5% for feedforward multilayer perceptron, and support vector machine respectively. From this experiment we discovered that support vector machine is the best network for the diagnosis of heart disease.

Cite This Paper

Ebenezer Obaloluwa Olaniyi, Oyebade Kayode Oyedotun, Khashman Adnan, "Heart Diseases Diagnosis Using Neural Networks Arbitration", International Journal of Intelligent Systems and Applications(IJISA), vol.7, no.12, pp.75-82, 2015. DOI:10.5815/ijisa.2015.12.08

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International Journal of Intelligent Systems and Applications (IJISA)