Int J Cur Res Rev | Vol 12 • Issue 22 • November 2020 162 Corresponding Author: Sharana Dharshikgan Suresh Dass, Asia Pacifc University of Technology and Innovation. ISSN: 2231-2196 (Print) ISSN: 0975-5241 (Online) Received: 22.08.2020 Revised: 20.09.2020 Accepted: 05.11.2020 Published: 24.11.2020 Research Article International Journal of Current Research and Review DOI: http://dx.doi.org/10.31782/IJCRR.2020.122227 INTRODUCTION The novel coronavirus disease (COVID-19) has created tre- mendous chaos around the world, affecting people’s lives and causing a large number of deaths. Its first cases were detected in Wuhan, China in December 2019 and now it has been spread to almost every country. Governments of many countries have proposed policies to mitigate the impacts of the COVID-19 pandemic. Science and technology have con- tributed significantly to the implementations of these poli- cies during this unprecedented and chaotic time. The coronavirus (COVID-19) has made exceptional clut- ter around the world. The primary case was distinguished in Wuhan, China in December 2019 and it has been spread all around the world. Distinctive arrangements and rules are proposed concerning dealing with COVID-19 by govern- ments. Science and innovation have supported. Early detec- tion and evaluation of infected patients have been considered by most of the computer science researchers. The artificial intelligence (AI) and different related computational tech- niques play a considerable role for this purpose. In general, when detecting disease at the later stage is much complicated to treat compared to detecting the disease at an earlier stage. The same concept applies to detect COVID-19. Based on the Malaysian newspaper (The STAR, 2020) the main cause of death in Malaysia due to COVID-19 is because of late treatment. 1 This also means that the patients were diagnosed with the virus very much later and not in the beginning stage. Also, late detection of the virus might put other people live at risk. This is because when the potential patient does not know if he or she is infected with the virus, they might carry on with their daily routine and spreading the virus to others. Besides that, when there is a delay in the detection of viruses in older people and those with underlying medical problems like cardiovascular disease, diabetes, chronic respiratory disease, and cancer, they are more likely to develop seri- ous illness. 2 This also increases the workload of the front liners in the medical field as the treatments for these cases are much more complicated than the normal cases suffer- ing from COVID-19 and require more and special attention and medical care. Furthermore, the reason why the current detection method is not so efficient is that multiple processes need to be carried out before an actual result can be obtained. Based on NPR Choice report in 2020, the first step that needs to be carried out is to take a sample from a patient’s nose or throat, using a special swab. That swab goes into a tube and is sent to a lab. 3 Small hospitals mostly send their samples to . ABSTRACT COVID-19 is an illness caused by a novel coronavirus also known as severe acute respiratory syndrome coronavirus 2, which was first identified in the City of Wuhan, China. Since then, it has been declared as a global pandemic by the World Health Or- ganization. The late diagnosis of COVID-19 patients makes the fast spreading of the virus across the globe. Purpose: Thus, the solution to slow down the spread of this virus would be an expert system that will be able to diagnose COVID - 19 patients and produce results instantly. This paper discusses how a knowledge-based expert system can help to diagnose or detect COVID – 19 in the early stage itself and get the result immediately without any delay. Key Words: Artificial intelligence, Expert system, Medical diagnosis, Hybrid intelligent systems, Knowledge acquisition, COVID-19 Expert System for Early Diagnosis of COVID - 19 Sharana Dharshikgan Suresh Dass 1 , Fatemeh Meskaran 1 , Mitra Saeedi 1 1 Asia Pacific University of Technology and Innovation. IJCRR Section: Healthcare Sci. Journal Impact Factor: 6.1 (2018) ICV: 90.90 (2018) Copyright@IJCRR