Detection and Analysis of Depression in Women Using Machine Learning Approaches

Abstract - Depression is a widespread mental health condition marked by ongoing sadness, reduced interest in activities, and emotional detachment. Unlike normal mood changes, it significantly impacts daily life, relationships, and productivity. This study presents a new, more reliable approach for identifying depression, which was tested using the Mental Screen Inventory. The method showed improved accuracy over existing techniques. The findings offer valuable insights for mental health professionals and researchers aiming to better understand and manage depression.

computer science AI&ML

1. A. Benton, M. Mitchell, and D. Hovy, “Multi-task learning for mental health using Machine Learning. [Google Scholar] [Crossref]

2. Paul, R., Muhammad, T., Rashmi, R. et al. Depression by gender and associated factors among older adults in India: implications for age- friendly policies. Sci Rep 13, 17651 (2023). https://doi.org/10.1038/s41598-023-44762-8. [Google Scholar] [Crossref]

3. A. G. Reece, A. J. Reagan, K. L. M. Lix, P. S. Dodds, C. M. Danforth, and E. J. Langer, “Forecasting the onset and course of mental illness with Twitter data,” Sci. Rep., vol. 7, no. 1, pp. 1–11, Dec. 2017. [Google Scholar] [Crossref]

4. A. H. Orabi, P. Buddhitha, M. H. Orabi, and D. Inkpen, “Deep learning for depression detection of Twitter users,” in Proc. 5th Workshop Com- put. Linguistics Clin. Psychol., From Keyboard Clinic, 2018, pp. 88–97. [Google Scholar] [Crossref]

5. A. T. Beck, C. H. Ward, M. Mendelson, J. Mock, and J. Erbaugh, “An inventoryfor measuring depression,” Arch. Gen. Psychiatry, vol. 4, no. 6, pp. 561–571, 1961. [Google Scholar] [Crossref]

6. A. Vaswani et al., “Attention is all you need,” in Proc. NIPS, 2017, pp. 1–1. [Google Scholar] [Crossref]

7. Adamou, M.; Antoniou, G.; Greasidou, E.; Lagani, V.; Charonyktakis, P.; Tsamardinos, I. Mining free-text medical notes for suicide risk assessment. In Proceedings of the 10th Hellenic Conference on Artificial Intelligence, Patras, Greece, 9–12 July 2018; pp. 1–8. [Google Scholar] [Google Scholar] [Crossref]

8. Affective and Content Analysis of Online Depression Communities Thin Nguyeny, Dinh Phungy, IEEE Member, Bo Daoy, Svetha Venkateshy, IEEE Fellow, Michael Berkzy [Google Scholar] [Crossref]

9. Akhiat, Y., Asnaoui, Y., Chahhou, M., & Zinedine, A new graph feature selectionapproach. In 2020 6th IEEE Congress on Information Science and Technology (CiSt) (pp. 156-161). IEEE. (2021, June). [Google Scholar] [Crossref]

10. Akhiat, Y., Chahhou, M., & Zinedine, A. Ensemble feature selection algorithm. International Journal of Intelligent Systems and Applications, 11(1), 24. (2019). [Google Scholar] [Crossref]

11. Akhiat, Y., Chahhou, M., & Zinedine, A. Feature selection based on graph representation. In 2018 IEEE 5th International Congress on Information Science and Technology (CiSt) (pp. 232-237). IEEE. (2018, October) [Google Scholar] [Crossref]

12. Akhiat, Y., Manzali, Y., Chahhou, M., & Zinedine, A New Noisy Random Forest Based Method for Feature Selection. Cybernetics and Information Technologies,21(2), 10-28. (2021). [Google Scholar] [Crossref]

13. Alam, S., Abdullah, M., Khan, F. N., Ullah, A. A., Rahi, M. M. I., Alam, M. A. (2019, December). An Efficient Image Processing Technique for Brain Tumor Detection from MRI Images. In 2019 IEEE Asia-Pacific Conference on Computer Science and Data Engineering (CSDE) (pp. 1-6). IEEE. [Google Scholar] [Crossref]

14. Albert Rizzo, Russell Shilling, Eric Forbell, Stefan Scherer, Jonathan Gratch, and Louis-Philippe Morency. Autonomous virtual human agents for healthcare information support and clinical interviewing. 2016. [Google Scholar] [Crossref]

15. Saurabh Chauhan, Dharamveer Singh, Atul Kumar Singh (2022) “Artificial Intelligence In The Military: An Overview Of The Capabilities, Applications, And Challenges”, Journal of Survey in Fisheries Sciences, Vol 9 (2) pp 984-991. https://doi.org/10.53555/sfs.v9i2.2911 [Google Scholar] [Crossref]

16. Kiran, Dharamveer Singh, Nitin Goyal, (2023) “Analysis Of How Digital Marketing Affect By Voice Search”, Journal of Survey in Fisheries Sciences, Vol. 30 (2) 407-412. https://doi.org/10.53555/sfs.v10i3.2890 [Google Scholar] [Crossref]

17. Yukti Tyagi, Dharamveer Singh, Ramander Singh, Sudhir Dawra (2024) “Analysis of The Most Recent Trojans On the Android Operating System”, Educational Administration: Theory and Practice, Vol. 30(2) 1320-1327. https://doi.org/10.53555/kuey.v30i2.6846 [Google Scholar] [Crossref]

18. Shivanee Singh, Dharamveer Singh, Ravindra Chauhan (2023) “Manufacturing Industry: A Sustainability Perspective on Cloud And Edge Computing”, Journal of Survey in Fisheries Sciences, pp 1592-1598. https://doi.org/10.53555/sfs.v10i2.2889 [Google Scholar] [Crossref]

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