MeDevice: A Mobile – Based Diagnosis of Common Human Illnesses using Neuro – Fuzzy Expert System

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Johaira U. Lidasan 1,* Martina P. Tagacay 1

1. Notre Dame University, Cotabato City, 9600, Philippines

* Corresponding author.


Received: 25 Apr. 2019 / Revised: 17 May 2019 / Accepted: 23 May 2019 / Published: 8 Aug. 2019

Index Terms

Fever, Neuro-fuzzy expert, hybrid system, Gradient descent, optimization algorithm


Fever is a sign that the body is trying to fight infection. It is usually accompanied by various sicknesses or symptoms that signal another illness or disease. Diagnosing it ahead of time is essential because it has to do with human life and to determine what to do to get well. MeDevice is a mobile-based application that runs in Android devices that allows the user to enter the levels of his/her symptoms and diagnoses the disease either as influenza, dengue, chicken pox, malaria, typhoid fever, measles, Hepatitis A and pneumonia together with its details and its first aid treatment. It aims at providing an efficient decision support platform to aid people with fever in diagnosing their disease and whether or not to seek medical attention especially in developing countries like the Philippines. This application is engineered with the knowledge base and the inference method of fuzzy logic and expert system with the help of Gradient Descent optimization algorithm and back propagation neural network to achieve the optimum value of the error rate. This is essential to provide the application with a high accuracy rate which shows during the conduct of testing of the application.

Cite This Paper

Johaira U. Lidasan, Martina P. Tagacay, "MeDevice: A Mobile – Based Diagnosis of Common Human Illnesses using Neuro – Fuzzy Expert System", International Journal of Information Technology and Computer Science(IJITCS), Vol.11, No.8, pp.27-32, 2019. DOI:10.5815/ijitcs.2019.08.04


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