Medical Expert System for Diagnosis of Abdominal Disorders

Abstract

Artificial Intelligence (Al) is the area of computer science concerned with the emulation of human thought processes. Efforts in the application of Al methods to intelligent problem solving led to the development of expert systems, systems which perform tasks that require a great deal of specialized knowledge that experts in a particular field acquire from long experience with such tasks. Expert systems are used extensively in many domains ranging from medicine to science and space technology. Many rural communities have an extremely limited access to medical advice. People travel long distances to clinics or medical facilities and there is a shortage of medical experts in most of these facilities. This results in slow service and patients end up waiting long hours without receiving any attention. This problem can be solved by creating a system that can give advice for common conditions such as abdominal diseases. Hence medical expert systems can play a significant role in such cases where medical experts are not readily available. In this, aspects of the design of an intelligent medical system for diagnosis of Common disease that can be detected by expert analysis and research on history. A number of patient cases are selected as prototype. The knowledge acquired from history review and human experts of the specific domain and is used as a base for analysis, diagnosis and recommendations. All the acquired knowledge is represented through hierarchal data chart that combines with production rules and Bayesian network rules. This results in better representation, and facilitates knowledge acquisition and maintenance. Diagnosis is performed through the hierarchal charts, based on patient data and expert analysis. The proposed system will be experimented on various scenarios in order to evaluate its performance.