Development of a Prototype of a Medical Application Using a Type-2 Fuzzy Inference System

The report presents a prototype of a medical fuzzy expert system developed for predicting the possibility of infection with COVID-19. The knowledge base of the expert system was developed using the PySwip software library. We used the framework to develop the user interface which provided the construction of the graphical shell of the expert system. The presented software system is able to receive and process users’ medical data and assess the likelihood of infection of the patient. For a development of the expert system we applied the type 2 fuzzy inference rules. The distinguishing feature of fuzzy inference rules is the possibility of working with incomplete information, which appears to be very important in the medical diagnostics. The implementation of software product was carried out using the Python programming language and has been practically tested in the different operational environments.