A Web Based Fuzzy Expert System for Human Disease Diagnosis

Author(s):  
Ms. Kalyani Baghel ◽  
◽  
Mr. Neeraj Mehta ◽  
2015 ◽  
Vol 37 ◽  
pp. 239
Author(s):  
Sadaf Anbarzadeh ◽  
Hossein Davari

Automatic disease diagnosis has been human concern for a long time. Since people are so busy and the doctors visit expenses areso expensive, a lot of different attempts have been done in the field of design of expert system for disease diagnosis. This paper describes aproject work aiming to develop a web based fuzzy expert system for human disease diagnosis. This program models the thinking pattern andhuman activity and leads to close the expert system and human action method. In this paper we have consulted with different physicians andanalyzed the diagnosis procedure and modeled them with a fuzzy expert system. This project is based on development of a web-based clinicaltool designed to improve the quality of the exchange of health information between health care professionals and patients . This system hasbeen tested on five diseases with sort throat symptom such as mononucleosis, scarlet fever, pharyngitis or tonsillitis, common cold and virusinfection and exhibited satisfactory results.


2018 ◽  
Vol 10 (3) ◽  
pp. 239-248
Author(s):  
S. Konyeha ◽  
F. A. Imouokhome

An expert system imitates the decision–making adeptness of a human expert. They are intended to answer complicated questions characterized mainly as if–then rules instead of traditional procedural code. A major problem facing the cultivation of rubber (Hevea brasiliensis) in developing countries is the destructive effect of pathogens which result in about fifty percent (50%) loss in crop yield. This problem persists, due to a communication gap between agricultural researchers, such that field extension officers, and farmers are hampered by various operational and logistic challenges. This paper is an effort to bridge this gap, and hence features an expert system that can be accessed online by farmers.  The expert system allows farmers to select disease symptoms presented in categories from a JAVA based user friendly graphical interface. The output generated by the rule–base engine, diagnoses the diseases of the rubber crop, and suggests curative and preventive measures. The main source of information for developing the expert system’ knowledge–base was the Rubber Research Institute, Iyanomo, Edo State, Nigeria.


2013 ◽  
Vol 11 (1) ◽  
pp. 161-168 ◽  
Author(s):  
Vahid Rafe ◽  
Mahdi Hassani Goodarzi

Sign in / Sign up

Export Citation Format

Share Document