Data mining in diagnosis of major depression disorder

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Masume Bakhtiari

Islamic Azad University of Hamedan, Iran

: J Comput Eng Inf Technol

Abstract

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In this research, we are trying to design a model of clinical decision support system (CDSS) for diagnosis of major depressive disorder (MDD). The methodology followed is research and development (R&D). To provide the needed data for diagnosis, a specific inventory has been made based on the necessary criterion of the fifth version of the diagnostic and statistical manual of mental disorders (DSM-5), case history and psychology condition examination. We use data mining as a modeling and testing tool. MLP neural network was used to evaluate accuracy. Evaluation criteria are confusion matrix and area under curve. 80% of the data are educational and 20% are experimental. Results are obtained for an average of 10 times. Finally, model predicts bing of disorder or not with acceptable accuracy.

Biography

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Masume Bakhtiari completed her Computer Software Engineering from the Arak branch of Azad University. She also has a Master’s Degree in Clinical Psychology. She has an accepted article in 6th Congress of Iranian Psychology, October 2017, Tehran, Iran and another in ICPCE Conference, December 2017, Mashhad, Iran.

E-mail: bakhtiarimasume@gmail.com