CFP last date
20 January 2025
Call for Paper
February Edition
IJCA solicits high quality original research papers for the upcoming February edition of the journal. The last date of research paper submission is 20 January 2025

Submit your paper
Know more
The week's pick
Responsive image
SFLA-Based Line Balancing and Task Optimization in Master-Slave Controlled Hanger Transportation Systems for Garment Production

Duc Hoang Nguyen
Random Articles
Reseach Article

A Neuro-Fuzzy System for Modeling the Depression Data

by Subhagata Chattopadhyay, Nirmal Baran Hui, Anish Dasari
journal cover thumbnail

International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 54 - Number 6
Year of Publication: 2012
Authors: Subhagata Chattopadhyay, Nirmal Baran Hui, Anish Dasari
10.5120/8567-2276

Subhagata Chattopadhyay, Nirmal Baran Hui, Anish Dasari . A Neuro-Fuzzy System for Modeling the Depression Data. International Journal of Computer Applications. 54, 6 ( September 2012), 1-6. DOI=10.5120/8567-2276

@article{ 10.5120/8567-2276,
author = { Subhagata Chattopadhyay, Nirmal Baran Hui, Anish Dasari },
title = { A Neuro-Fuzzy System for Modeling the Depression Data },
journal = { International Journal of Computer Applications },
issue_date = { September 2012 },
volume = { 54 },
number = { 6 },
month = { September },
year = { 2012 },
issn = { 0975-8887 },
pages = { 1-6 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume54/number6/8567-2276/ },
doi = { 10.5120/8567-2276 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T20:54:58.157539+05:30
%A Subhagata Chattopadhyay
%A Nirmal Baran Hui
%A Anish Dasari
%T A Neuro-Fuzzy System for Modeling the Depression Data
%J International Journal of Computer Applications
%@ 0975-8887
%V 54
%N 6
%P 1-6
%D 2012
%I Foundation of Computer Science (FCS), NY, USA
Abstract

Depression is a psychological disorder, which, if untreated, may deteriorate the quality of one's life. Therefore, to tackle it, its early screening and accurate grading are much needed. The success of soft computing largely stands on its effective ways of handling uncertainty, which is often encountered in a clinical diagnosis. This paper proposes application of soft computing techniques to automate depression diagnosis. In order to achieve our goal, an intelligent Neuro-Fuzzy model has been developed. It has been trained with a sample of real-world depression data. Experiments with test data reveal that the Mean Squared Error in prediction is nominal for most of the cases. Such a system could assist the doctors to take decisions in much needed situations.

References
  1. J. H Li, L. Land, P. Ray and S. Chattopadhyay, "E-Health readiness framework from electronic health records perspective", IJIEM, vol. 6, pp. 326-348, 2010.
  2. S. D. Shapiro, "Merging personalized medicine and biology of aging in chronic obstructive pulmonary disease" Am J Respir. Crit. Care Med, vol. 184, pp. 864-866. 2011.
  3. J. M. Tenório, A. D. Hummel, F. M. Cohrs, V. L. Sdepanian, I. T. Pisa, and H. de-F. Marin, "Artificial intelligence techniques applied to the development of a decision-support system for diagnosing celiac disease", IJMI, vol. 80, pp. 793-802, 2011
  4. Y. Wang, H. Yan, R. Guo, F. LI, C. Xia, J. Yan, Z. Xu, G. Liu and J. Xu, "Study on intelligent syndrome differentiations in traditional Chinese medicine based on multiple information fusion methods", IJDMB, vol. 5, pp. 369-382, 2011.
  5. S. Chattopadhyay, D. K. Pratihar, S. C. DeSarkar, "Fuzzy logic-based screening and prediction of adult psychoses: a novel approach", IEEE Trans. Syst. Man Cybernetics Part-A, vol. 39, pp. 381-387, 2009.
  6. S. Chattopadhyay, D. K. Pratihar, "Towards developing intelligent autonomous systems in psychiatry: its present state and future possibilities", Intelligent Autonomous Systems Studies in Computational Intelligence, vol. 275, pp. 143-166, Springer 2010.
  7. A. Carson, "The human illnesses: neuropsychiatric disorders and the nature of human brain", BJPsych. , vol. 200, p. 85, 2012.
  8. A. Bramesfeld, T. Grobe, F. W. Schwartz, "Prevalence of depression diagnosis and prescription of antidepressants in East and West Germany: an analysis of health insurance data", Social Psychiatry and Psychiatric Epidemiology, vol. 45, pp. 329-335, 2010. [last accessed on 08/03/2012]
  9. WHO: Mental Health and Substance Abuse. URL: http://www. searo. who. int/en/Section1174/Section1199/Section1567/Section1826_8101. htm [last accessed on 08/03/2012]
  10. O. J. Robinson, C. Overstreet, A. Letkiewicz, and C. Grillon, "Depressed mood enhances anxiety to unpredictable threat", Psychological Medicine, pp. 1-11, (online first) DOI: 10. 1017/S0033291711002583, 2011.
  11. L. Eloul, A. Ambusaidi, and S. Al-Adwai, "Silent epidemic of depression in women in the Middle East and North Africa region,", Sultan Qaboos Univ. Med J, vol. 9, pp. 5-15, 2009.
  12. A. K. Surbey, "Adaptive significance of low levels cooperation in depression", Evolution and Human Behavior, vol. 32, pp. 29-40, 2011.
  13. S. Titmarsh and I. Goodyer, "Psychiatric diagnosis needs a more scientific approach", Progress in Neurology and Psychiatry, vol. 15, pp. 21-22, 2011.
  14. B. M. Kwan, S. Dimidjian, and S. L. Rizvi, "Treatment preference, engagement, and clinical improvement in pharmacotherapy versus psychotherapy for depression", Behaviour Research and Therapy, vol. 48, pp. 799-804, 2010.
  15. S-C. Yu and U. H. Lin "Applications of fuzzy theory on health care: an example of depression disorder classification based on FCM," WSES Transactions of Information Science and Applications, vol. 5, pp. 31-36, 2008.
  16. S. Chattopadhyay, D. K. Pratihar, and S. C. De Sarkar "Some studies on fuzzy clustering of psychoses data," International Journal of Business Intelligence and Data mining, vol. 2, pp. 143-159, 2007.
  17. S. Chattopadhyay P. Kaur, F. Rabhi, and U. R. Acharya "Neural Network Approaches to Grade Adult Depression ," Journal of Medical Systems , vol. 36, issue 5, pp. 2803-2815, 2011.
  18. Y-M Tai, and H-W Chiu "Artificial Neural Network Analysis on Suicide and Self-Harm History of Taiwanese Soldiers," in Second International Conference on Innovative Computing, Information and Control, 2007 (ICICIC'07) pp. 363 – 363, 2007.
  19. Chattopadhyay S. , –"Neurofuzzy Models to Automate the Grading of Old-age Depression". Expert Systems: the Journal of Knowledge Engineering (2012); (in press).
  20. Chattopadhyay S. , – "A Prototype Depression Screening Tool for Rural Healthcare: A Step towards e-Health Informatics", Journal of Medical Imaging and Health Informatics (2012), in press
  21. Chattopadhyay S. , Banerjee S. , Rabhi F. A, Acharya R. U. – "A Case-based Reasoning System for Complex Medical Diagnoses". Expert Systems: the Journal of Knowledge Engineering (2012); DOI: 10. 1111/j. 1468-0394. 2012. 00618. x (in press).
  22. Chattopadhyay S. , Acharya U. R. "A Novel Mathematical Approach to Diagnose Premenstrual Syndrome", Journal of Medical Systems (2012); 36(4): 2177-2186.
  23. E. H. Mamdani, and S. Assilian, "An experiment in linguistic synthesis with a fuzzy logic controller", International Journal of Man-Machine Studies, vol. 7, pp. 1-13, 1975.
  24. N. B. Hui, V. Mahendar, and D. K. Pratihar, "Time-optimal collision-free navigation of a car-like robot using a neuro-fuzzy approach", Fuzzy Sets & Systems, vol. 157, pp. 2171-2204, 2006.
  25. F. Smit, H. van Hout, P. van Oppen, H. van der Horst, A. and Beekman, H. van Marwijk, "Cost-effectiveness of a stepped care intervention to prevent depression and anxiety in late life: randomized trail", BJPsych, vol. 196, pp. 319-325, 2010.
Index Terms

Computer Science
Information Sciences

Keywords

Mental Health Informatics Depression Data Neuro-Fuzzy Modeling

Powered by PhDFocusTM