Designing an expert system for diagnosis of TB

Today, “Computer Decision Support Systems” are designed and used in various fields of science. In this new atmosphere, “Expert Systems”, as a sub-branch of Artificial Intelligence, play a central role. In Expert Systems, decisions are made by the computer [1]. Expert Systems are knowledge-based systems that initially acquire knowledge from an expert person, and then transfer it to the computer, so that by making decisions based on the data collected, they can be of help to humans. So far, many Expert Systems have been presented in various fields like industry, control, space, financial decisions, etc [2]. Expert Systems have also found their way into medicine. For example; Dendralsoftware program (1965) to describe and express molecular structure [3], MYCIN software (1976) for diagnosis of coronary heart diseases [4], VM for monitoring Intensive Care patients [1], CADCUCEUS for diagnosing internal medicine related diseases [1], BLUEBOX for diagnosis and treatment of depression [1], as well as systems that detect acidic electrolytes, andmanagement of anesthesia education [1]. Our aim is to present an Expert System for diagnosing TB. A medical Expert System is a computer program that helps with decision making for diagnosis of diseases and suggests treatment methods. Once patient’s data are entered, the system performs diagnosis of disease, predicts potential complications, and suggests treatment method. These systems are distinct from other medical software, since, to arrive at a medical result, they imitate the rationale of an expert physician. Expert systems require many rules and facts of medical science about diseases and condition of the disease to be able to make decisions and present accurate results.