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The recent pandemic caused by the Coronavirus Disease (COVID-19) first surfaced in Wuhan, China in December 2019. This paper presents an expert system for the diagnosis of COVID-19 based on its symptoms to aid people in taking precautionary measures. When experts are not available, an expert system that can effectively diagnose the disease is crucial. It takes the place of one or more experts in decision-making and problem-solving. An expert system for diagnosis of COVID-19 is a system developed to recognize early COVID-19 symptoms that individuals may experience by allowing users to directly check the disease with results that can serve as a foundation for additional testing. This study's primary goal is to identify useful COVID-19 detection patterns or knowledge by examining the historical data we have obtained from the Kaggle dataset. The patterns are presented as rules, which are given to the expert system after consultation with a domain expert. A total of 1,048,575 pieces of data were used for model training and testing. To detect COVID-19 disease, we employ a PART rule-based algorithm, which performed 92.47% accurately in a 10-fold cross-validation test. We can therefore draw the conclusion that the algorithm produces a promising result and that the expert system aids in the diagnosis of the disease. The system offers a suggestion in line with the identified symptom. [ABSTRACT FROM AUTHOR]

Introduction: Coronavirus disease 2019 (COVID-19) is a novel coronavirus that was frequently isolated from Wuhan, China in patients with respiratory tract infections. The most prevalent symptoms are fever and respiratory tract involvement. In this paper, seizures, an uncommon manifestation of the condition, is described. Case Discussion: A previously healthy 34-year-old female was taken to the emergency room with a widespread tonic-clonic seizure. Five days prior to admission, the patient complained of fever, cough, headache, widespread weakness, and myalgias. She experienced two episodes of convulsions around one hour ago. The MRI of the brain was normal, whereas the CT of the chest indicated localised ground-glass opacities. Using real-time PCR, the respiratory material was positive for COVID-19. The patient's symptoms improved after using anticonvulsive and antiviral drugs. Conclusions: To our knowledge, this is one of the rare case studies reporting a link between frequent seizures and COVID - 19. [ABSTRACT FROM AUTHOR]