A rule-based expert system for rapid problem solving in crowded outpatient clinics in Egypt

摘要

A rule-based expert system was developed to help health personnel working in crowded outpatient clinics in Egypt make rapid and accurate diagnosis. In this system, the medical knowledge of more than 300 major and minor common diseases is encoded in the form of production rules. These rules are invoked in groups according to one or more presenting symptoms, and diagnostic hypotheses are formulated for the diseases most likely to cause these symptoms. Hypothesis for the less common but more serious diseases are tested first to determine the order in which diseases are eliminated. Probability values are used to discriminate between competing disease hypotheses. Once a disease is identified, a recommendation is given for treatment or referral for further diagnosis. The system is developed in TURBO PROLOG on the IBM PC and provides simple facilities to acquire or update the medical knowledge and to explain its reasoning.