Advances in Applied Research
Year : 2009, Volume : 1, Issue : 1
First page : ( 69) Last page : ( 81)
Print ISSN : 0974-3839. Online ISSN : 2349-2104.

An efficient system to deduce depression using case-based reasoning and CHARM mining algorithm

Radha P.*, Ramaraj E.

Department of Computer Science and Engineering, Alagappa University, Karaikudi

*Corresponding Author: E Mail: radhameena@rediffmail.com

Online published on 11 June, 2014.

Abstract

This paper introduces a system for psychologists in assessing cases of depression and determines level of severity and finds all frequent symptoms using CHARM mining algorithm. This system has a user interface that requires the client's to answer multiple questions that corresponds to a specific symptom. The individual ratings and overall ratings of the symptoms go to a database containing data and diagnosis of patients for comparison. The existing system was implemented using rule-based reasoning. Due to some drawbacks case-based reasoning is used for comparing new cases with existing cases. Value difference metric function is used to retrieve nearest neighbor of the new case and the diagnosis of the nearest neighbor. With the founded symptoms, a large database is designed in order to find all frequent symptoms and it is used to reduce unnecessary symptoms from the database.

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Keywords

Depression, Rule Based Reasoning, Case Based Reasoning, Nearest Neighbor Algorithm, Value Difference Metric Function, CHARM mining Algorithm.

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