Expert System of Kawasaki Disease Diagnosis

Authors

  • Nur Alyaa Athira Md Zamree Universiti Tun Hussein Onn Malaysia
  • Nureize Arbaiy Universiti Tun Hussein Onn Malaysia

Keywords:

Kawasaki Disease, Expert System, ESDLC

Abstract

Kawasaki disease that usually affects children is rare in Malaysia. However, awareness and diagnosis are important to know because they have cardiac involvement that can lead to death. It is also possible that the disease is not diagnosed as a result of lack of awareness of the disease and also symptoms similar to other diseases. Therefore, knowing the cause and effect of this disease is important. like most diseases, information is usually obtained from media sources and direct consultation from a health center. although good, the delivery of information is sometimes difficult to understand because users need to analyze or study for themselves whether there are symptoms or not. Thus, in this project a system that can perform self-diagnosis to identify the possibility of suffering from Kawasaki disease has been developed using an expert system approach. In addition to providing expert knowledge for public sharing, the system also acts as an alternative tool to raise awareness among the population. The Expert System Development Methodology (ESDLC) methodology is used as a system development guide. The front chain method is used to draw conclusions for the diagnosis process. Meanwhile, PHP and MySQL programming are used to develop the system. The system has the function of performing diagnostic tests for Kawasaki Disease through the interactive implementation of the system interface, database, knowledge base, and user communication. This system is expected to help in the process of self-diagnosis that can be done by individuals who resemble the actual process of diagnosis with a specialist.

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Published

05-06-2022

Issue

Section

Software Engineering

How to Cite

Md Zamree, N. A. A., & Arbaiy, N. . (2022). Expert System of Kawasaki Disease Diagnosis. Applied Information Technology And Computer Science, 3(1), 685-698. https://publisher.uthm.edu.my/periodicals/index.php/aitcs/article/view/2386