Expert System for the Timely Diagnosis of Infectious Diseases

Abstract

Infectious diseases such as COVID-19, dengue, diphtheria, etc., are spreading throughout the world, just like in Peru. Some of the symptoms of these diseases are similar. Rapid diagnosis is not available in this case, especially in regions with limited medical facilities. In addition, some people are unaware of the symptoms caused by these diseases. The objective of the research is to design a rule-based web expert system prototype using the Buchanan and Rational Unified Process (RUP) methodology and evaluate to determine the feasibility of building the system for early detection and timely treatment of infectious diseases such as COVID-19, Zika, Dengue, Diphtheria, Influenza, Chikungunya, and Monkeypox. The result was a prototype of an expert system with friendly and easy-to-use interfaces. In addition, the quality level of the prototype was evaluated through expert judgment, who analyzed the system's efficiency, usability, security, and functionality. After calculating the scores of the evaluated criteria, the total average was 4.74 out of 3, which is the minimum average for the feasibility of the expert system to be considered acceptable, considering the level of quality. In conclusion, it was possible to design and evaluate the expert system prototype. In addition, the results also show that it is feasible to build the proposed system for the early detection and treatment of infectious diseases for the benefit of people's health. © 2023 Elsevier B.V., All rights reserved.