Designing a Medical Fuzzy Expert System Using the JFuzzyLogic Library

• Published in: 2024 IEEE 25th International Conference of Young Professionals in Electron Devices and Materials (EDM) pp. 2330 - 2333
• Main Authors: Burnashev, Rustam A., Bagymanov, Ruslan M., Enikeeva, Adelya I., Farahov, Rustam R., Bolsunovskaya, Marina V.
• Format: Conference Proceeding
• Language: English
• Published: IEEE 28.06.2024
• Subjects: fuzzy expert systems; Fuzzy logic; intelligent search; Java; JFuzzyLogic; knowledge base; medical data; Medical information systems; Software algorithms; Software libraries; Software systems; Unified modeling language
• ISSN: 2325-419X
• DOI: 10.1109/EDM61683.2024.10615193

The article presents the processes of designing a medical expert system using software tools that work with fuzzy logic. Using a simplified fuzzy inference algorithm, it was possible to achieve the fuzziness of the system by creating a knowledge base of fuzzy rules that are adjusted to take into account changes in input data (fuzzification) and output data (defuzzification). The knowledge base was formed using the open source software library JFuzzyLogic (Java programming language). The study developed a UML activity diagram and identified the steps that researchers can use to create their own intelligent systems. A unified system that combines the components of a medical information system with the created knowledge base will contribute to more efficient data processing and analysis in scientific research. Filling and processing of the knowledge base of the expert system is available to an expert of the subject area. The created knowledge base includes all the necessary functions for processing fuzzy data, setting the necessary weights for input, output and data processing.