A Mobile-based Neuro-fuzzy System for Diagnosing and Treating Cardiovascular Diseases

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Folasade O. Isinkaye 1,* Jumoke Soyemi 2 Olayinka P. Oluwafemi 1

1. Ekiti State University/Department of Computer Science, Ado-Ekiti, Nigeria

2. Federal Polytechnic/Department of Computer Science, Ilaro, Nigeria

* Corresponding author.

DOI: https://doi.org/10.5815/ijieeb.2017.06.03

Received: 4 Nov. 2016 / Revised: 25 Nov. 2016 / Accepted: 16 Dec. 2016 / Published: 8 Nov. 2017

Index Terms

Heart disease, Neuro-fuzzy system, Artificial Neural network, Intelligence Technique, Android


In our present environment, heart diseases are very rampart and they describe the various types of diseases that affect the heart. They account for the leading cause of death word-wide especially, in Africa. It is therefore very important for individuals to have adequate knowledge about their heart health in order to avoid the risk of decreased life expectancy. The high mortality rate of heart (cardiovascular) diseases is attributed to the unequal ratio of patients to scarcity of medical experts who can provide medical care, also patients are not always warn to waiting long hours on queue in the hospital, especially in cases of emergency. This paper designed and implemented a Mobile Neuro-fuzzy System that uses the combination of the intelligence technique of Artificial Neural Networks (ANN) and the human-like reasoning style of Fuzzy Logic to diagnose and suggest possible treatments for cardiovascular diseases through interactivity with user. It employs programs like MySQL, PHP, JAVA (Android) and XML (Android Studio) while tools like XAMPP, PhpStorm and Android O/S were used to integrate these techniques together. The system, proved to be of enormous advantage in diagnosing heart diseases, as it diagnoses and learns about each user per time, to provide adequate and appropriate results and also makes reliable predictions to users.

Cite This Paper

Folasade O. Isinkaye, Jumoke Soyemi, Olayinka P. Oluwafemi, "A Mobile-based Neuro-fuzzy System for Diagnosing and Treating Cardiovascular Diseases", International Journal of Information Engineering and Electronic Business(IJIEEB), Vol.9, No.6, pp. 19-26, 2017. DOI:10.5815/ijieeb.2017.06.03


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