Depression Consultation Expert System

Minh Anh, Nguyen Thi (2006) Depression Consultation Expert System. [Final Year Project] (Unpublished)

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Abstract

Depression Consultation Expert System (DECES) is a web-based Diagnosis and
Counseling system for depression cases based on knowledge from human expert. Given
the shortage of psychiatrists, the refusal of patients on face-to-face consultation due to
shyness, appointment hassles, time& cost of each treatment, and a considerable increase
in numbers of depressive subjects, there is a definite sense of urgency in the development
of this system. The objectives of the project are to understand the underlying concepts of
AI in medicine in general and psychology in particular, and to develop DECES through
research on diagnostic expert system, its construction techniques and approaches. The
methodology used is expert system development life cycle with prototyping. The
development begins with knowledge acquisition, then design of the knowledge base and
inference methods. Application of this methodology allows the prototype to be evaluated
and refined by professionals in stages to verify its credibility, reliability and clinical
acceptability. The system is able to guide its users to a diagnosis process of identifying
their depression levels and causes and getting self-help without the intervention of
psychiatrists. The proposed system captures the expertise, which empowers patients with
the ability to help themselves in depression treatment quickly, at any convenient place
and time. With the increase recognition of the seriousness of depression and the
importance to reduce it critically, the future depression expert system appears to be
promising and optimistic. This paradigm shift makes depression consultation expert
system an emerging and ever-evolving one that can be and should be productively
explored.

Item Type: Final Year Project
Subjects: Z Bibliography. Library Science. Information Resources > ZA Information resources
Departments / MOR / COE: Sciences and Information Technology
Depositing User: Users 2053 not found.
Date Deposited: 27 Sep 2013 10:57
Last Modified: 25 Jan 2017 09:46
URI: http://utpedia.utp.edu.my/id/eprint/6894

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