Classification of Diseases of The Urinary System using an Expert System - Gatto, Dacyr Dante de Oliveira; Reis, João Victor Oliveira Mendonça; Pedro, Leandro Rosa; dos Santos, Winicios Alves; Farias, Edquel Bueno Prado (Revista Gestão da Produção Operações e Sistemas, 2021)
Purpose – Develop and use an Expert System (ES) to classify diseases of the urinary system. Design/methodology/approach – Computational experiments were divided into three phases, as described: Phase A: Database selection: We searched for a database that contains information on diseases of the urinary system. Phase B: Development and Implementation of the Expert System: Rules and variables were planned for the correct data manipulation, and the Expert System was created by implementing the rules and variables. Phase C: Validation of the Expert System: Expert System validated by specialists. Findings – The Expert System was validated by a general practitioner and, as such, was successful while carrying out the tests and results. In conclusion, the Expert System was generated to classify two diseases (Cystitis and Nephritis) of the urinary system. This was validated by a general practitioner who confirmed the accuracy of the information within the system developed and aimed of assisting the field of medicine for a specific organ. Originality/value – The development of the present work has made it possible to assist the specific diagnosis of two diseases of the urinary system. With the assistance of the Specialist System, professionals can be more confident when diagnosing diseases of the urinary system in patients. Keywords - Urinary System; Expert Systems; Artificial Intelligence; Support to The Diagnosis.