FACILITATION AND ACCELERATION OF DIAGNOSIS AND TREATMENT OF COVID-19 USING AN EXPERT SYSTEM
ATEFEH HASAN-ZADEH *
Fouman Faculty of Engineering, College of Engineering, University of Tehran, Iran.
MOHAMMADREZA FARAJI
Computer Engineering, Fouman Faculty of Engineering, College of Engineering, University of Tehran, Iran.
*Author to whom correspondence should be addressed.
Abstract
This study examines the forward method for establishing an expert system for the diagnosis of COVID-19 disease in the Python environment. To do this, first the tree related to this expert system is drawn. The laws of Knowledge Tree in expert system is designed to treat all known symptoms for the diagnosis of COVID-19, including severe fever and headache, dry cough, losing the sense of smell and taste, fatigue, sore throat and shortness of breath (asthma). Based on the drawn tree, the studied expert system is designed considering its general architecture consisting of inference engine, knowledge base, and result description, working memory, external programs, constructor interfaces and user interfaces. This in turn will be a good supportive aspect along with the methods of diagnosis by the physician, PCR, CT scan and serology to be effective in facilitating and accelerating the diagnosis and treatment.
Keywords: Expert system, knowledge base, COVID-19, backward-chaining and forward-chaining