Expert System for Diagnosing Human Psychological Disorders Using the Forward Chaining Method

Abstract

This study aims to design an expert system capable of providing early diagnosis of human psychological disorders using the Forward Chaining method. The research was conducted through a literature review, the development of a knowledge base, and the formulation of rule-based diagnostic structures derived from psychological references, including the DSM-5. The system is designed to identify eight common psychological disorders using twenty primary symptoms that are mapped into IF–THEN rules. The inference process operates by matching user-selected symptoms with the rules contained in the knowledge base. The results indicate that the Forward Chaining method can systematically and logically generate early diagnostic indications for disorders such as depression, anxiety, bipolar disorder, PTSD, and others. A case simulation demonstrates that the reasoning mechanism is able to produce accurate conclusions based on the combination of symptoms entered. Although the system has not yet been implemented as a software application, this study confirms that the conceptual design of an expert system using Forward Chaining can serve as an effective tool for early mental-health detection and has strong potential for further development.