Proceedings of the Annual Conference of JSAI
Online ISSN : 2758-7347
35th (2021)
Session ID : 4N3-IS-1b-01
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Design and implementation of a SWI-Prolog-based expert system to diagnose anxiety disorder
Che-Chern LIN*Kairen CHEN
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Abstract

Anxiety disorder is a common mental disorder that affects people's daily life, and causes problems in social activities. Traditionally, doctors have relied on questioning symptoms, observing patients, and even using questionnaires to diagnose and treat their patients, lacking a knowledge framework for detailed and rapid diagnosis. Therefore, an easy-to-use expert system to diagnose anxiety would be very helpful to mental doctors, thus reducing doctors’ workload. SWI-Prolog is one of the popular expert system programming languages for building expert systems. Based on Diagnostic and Statistical Manual of Mental Disorders, Fifth Edition (DSM–5) which is a common and useful guidebook for diagnosing mental disorders, this study designed and implemented an expert system for diagnosing anxiety disorders using SWI-Prolog and Java. This study also briefly introduces the basic syntax of SWI-Prolog, and explains how to connect Java and SWI-Prolog, in order to provide better visualization for users.

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© 2021 The Japanese Society for Artificial Intelligence
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