Expert systems are a branch of artificial intelligence that emulates human reasoning. It is made Up of a set of components, including an inference engine and a knowledge base. The expert systems are developed for specific well-defined domains achieving better results than humans. the expert systems act as assistants and complex auxiliaries of great utility, providing effective help in those jobs that requires precision, speed and high knowledge for decision making. On medicine field, expert systems are being used as a support tool for the diagnosis of diseases. In this article we present a case an study of a prototype of an expert system to support the diagnosis of chronic kidney diseases and the urinary tract. The prototype built of the expert system is based on an architecture of software applications to perform different functions ranging from the development of the graphical interface for interaction with the user, the reasoning engine, the construction of the knowledge base obtained from experts in urology and nephrology. The prototype is designed to support the work of general medicine, in the first stage of patient screening in the hospitals' offices before referring it to a specialist. The system recommends a diagnosis according to the symptoms presented by the patient. The prototype is currently in the testing phase. At the end of the article, the results of the proposed work are presented.
Se considera la enfermedad renal crónica (ERC), como una disminución progresiva de la función de los riñones de forma irreversible, a diferencia de la insuficiencia renal aguda en la que el daño presentado por los riñones es reversible. Los sistemas expertos actúan como asistentes y auxiliares complejos de gran utilidad, brindando ayuda efectiva en aquellos trabajos que requieren precisión, rapidez y alto conocimiento. Se presenta un prototipo de sistema experto, basado en una plataforma para el desarrollo de la interfaz gráfica integrada a un lenguaje de programación de reglas para asistir a las decisiones de un médico de medicina general para realizar un diagnóstico temprano y preciso de ERC. El sistema recomienda un diagnóstico de acuerdo a los síntomas que presenta el paciente.
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