Development of an Expert System Based on Fuzzy Logic for Pneumonia Diagnostics

The paper is devoted to the development of an expert system for the diagnosis of pneumonia based on fuzzy logic implemented using the Mamdani algorithm. It discusses the main stages of system development, including the fuzzification of input data, definition of fuzzy rules based on medical expert knowledge, the aggregation of fuzzy inferences, and their defuzzification to obtain the final diagnostic result. The system’s web interface is implemented using the Django framework, which ensures the ease of interaction for users. The use of a medical expert system for diagnosing pneumonia can reduce the time required to establish a diagnosis and improve its quality of integrating the experience of medical experts and modern information technologies.