An Online Expert System for Psychiatric Diagnosis

Abstract

Expert systems are programs that use artificial intelligence techniques, and simulate the performance of the human expert in a given area of expertise by collecting and using one or more expert information and expertise in a particular field. We developed declarative, online procedural rule-based expert system models for psychological diseases diagnosis and classification. The constructed system exploited computer as an intelligent and deductive tool. This system diagnoses and treats more than four types of psychiatric diseases, i.e., depression, anxiety disorder, obsessive-compulsive disorder, and hysteria. The system helps psychology practitioner and doctors to diagnose the condition of a patient efficiently and in short time. It is also very useful for the patients who cannot go to a doctor because they cannot afford the cast, or they do not have a psychological clinic in their area, or they are ashamed of discussing their situation with a doctor. The system consists of program codes that make a logic decision to classify the problem of the patient. The methodology for developing the declarative model was based on the backward chaining, also called goal-driven reasoning, where knowledge is represented by a set of IF-THEN production rules. The declarative programs were written in the PROLOG. While the design of the procedural model was based on using common languages like PHP, JavaScript, CSS, and HTML. The user of the system will enter the symptoms of the patients through the user interface and the program executes. Then the program links the symptoms to the pre-programmed psychological diseases, and will classify the disease and recommend treatment.

Keywords: Artificial Intelligence, Expert systems, Medical Diagnosis, Rules, Symbolic Reasoning, psychiatric diseases