Development of an Expert System Based on Fuzzy Logic for Pneumonia Diagnostics
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Abstract
The paper is devoted to the development of an expert system for diagnosing pneumonia based on fuzzy logic and implemented using the Mamdani algorithm. The paper discusses the main stages of the system development, including fuzzification of input data, definition of fuzzy rules based on medical expert knowledge, aggregation of fuzzy inferences and their defuzzification to obtain the final diagnostic result. The web interface of the system is implemented using the Django framework, which ensures 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 the quality of diagnosis by integrating the experience of medical experts and modern information technologies.
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References
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