Examination of an Expert System for Identifying the Singapore Flu Infectious Disease in Young Children the Dempster-Shafer Algorithm

Abstract

This research aims to develop an expert system that can detect the contagious Singapore flu in toddlers using the Dempster-Shafer algorithm. Singapore flu, caused by the enterovirus, often affects children, especially toddlers, with varying symptoms, including fever, rash, and oral ulcers. Early detection is crucial to reduce the impact of the spread of this disease. The expert system developed in this research utilises the Dempster-Shafer algorithm to process information and provide decisions based on the input symptom data. The Dempster-Shafer algorithm was chosen for its ability to handle uncertainty and deliver more accurate results in situations where the available information is incomplete or ambiguous. This research implements a computer-based system that can assist medical personnel in diagnosing Hand, Foot, and Mouth Disease (HFMD) by identifying symptoms present in toddler patients, as well as providing appropriate action recommendations based on the diagnosis results. The test results show that this system has high accuracy in detecting Hand, Foot, and Mouth Disease in toddlers, and can serve as an effective tool in improving the speed and accuracy of diagnosis, thereby supporting faster and more precise treatment. Thus, this expert system is expected to make a significant contribution to the prevention and control of Hand, Foot, and Mouth Disease in toddlers.