Fighting depression: psychological approaches among Bangladeshi university students

This thesis is submitted in partial fulfillment of the requirements for the degree of Bachelor of Science in Computer Science, 2022.

书目详细资料
Main Authors:	Sen, Sanjib Kumar, Apurba, Md. Shifatul Ahsan
其他作者:	Anwar, Md. Tawhid
格式:	Thesis
语言:	English
出版:	Brac University 2022
主题:	Depression Mental health Prediction Random forest Gaussian Naive Bayes Deep learning Neural networks Decision tree Support Vector Machine Machine learning Cognitive learning theory (Deep learning) Neural networks (Computer science)
在线阅读:	http://hdl.handle.net/10361/17137

id	10361-17137
record_format	dspace
spelling	10361-171372022-08-31T21:01:37Z Fighting depression: psychological approaches among Bangladeshi university students Sen, Sanjib Kumar Apurba, Md. Shifatul Ahsan Anwar, Md. Tawhid Department of Computer Science and Engineering, Brac University Depression Mental health Prediction Random forest Gaussian Naive Bayes Deep learning Neural networks Decision tree Support Vector Machine Machine learning Cognitive learning theory (Deep learning) Neural networks (Computer science) This thesis is submitted in partial fulfillment of the requirements for the degree of Bachelor of Science in Computer Science, 2022. Cataloged from PDF version of thesis. Includes bibliographical references (pages 56-58). In recent years, mental health deterioration cases have increased exponentially indicates that this issue needs our attention. Stressful situations of our daily life such as excessive study load, relationship predicaments, domestic abuse, sexual harassment, and many other reasons cause depression which is often prevalent and ends up causing physical or mental harm. The psychiatrists, psychoanalysts, and counselors are having a tough time dealing with large numbers of cases. They could only help some of the patients as most of them do not have access to them. Moreover, some people cannot bear the cost or feel hesitant to open up to them. In addition, the overall process takes a long time to understand the patient’s condition, and sometimes patients hide information from the counselors that lead to wrong assessment. Sometimes, it is too late to diagnose and treat their depression. As a result, they reach an extremely vulnerable stage and choose the path of self-harm that contributes to the increasing rate of suicide. Analyzing their history and then taking proper measurements can contribute to the treatment of depression. However, the challenge is that human behavior is ambiguous and inconsistent. Therefore, we propose methodologies for diagnosing their mental health conditions by tracking the probable cause of their depression. With the help of deep learning and machine learning, our goal was to analyze large data sets for observing patterns such as age, gender, the causality of depression, the delta of behavior changes, and many other things related to students and excavating things efficiently to help patients. When it comes to making predictions about depression and offering advice, the survey data that we have gathered over the course of this project has been of great assistance. According to the findings of our research, the Random Forest Classier Algorithm is capable of accurately predicting depression with an accuracy of 87%, an f-measure of 86%, and this model is also the best model. In comparison to the other algorithms that we used, such as K-Nearest Neighbor, Support Vector Machine, Gaussian Naive Bayes, Artificial Neural Network, Gradient Boost, and Decision tree, this one performed far better. The recommendation model that was built by us as part of this research project is our novel contribution to this discussion. We will prognosticate to assist the students with mobile application in the near future, so that they feel better with the help of Machine Learning and Deep Learning by inspecting and examining those patterns. Sanjib Kumar Sen Md. Shifatul Ahsan Apurba B. Computer Science 2022-08-31T08:12:22Z 2022-08-31T08:12:22Z 2022 2022-05 Thesis ID 19301101 ID 19301086 http://hdl.handle.net/10361/17137 en Brac University theses are protected by copyright. They may be viewed from this source for any purpose, but reproduction or distribution in any format is prohibited without written permission. 58 pages application/pdf Brac University
institution	Brac University
collection	Institutional Repository
language	English
topic	Depression Mental health Prediction Random forest Gaussian Naive Bayes Deep learning Neural networks Decision tree Support Vector Machine Machine learning Cognitive learning theory (Deep learning) Neural networks (Computer science)
spellingShingle	Depression Mental health Prediction Random forest Gaussian Naive Bayes Deep learning Neural networks Decision tree Support Vector Machine Machine learning Cognitive learning theory (Deep learning) Neural networks (Computer science) Sen, Sanjib Kumar Apurba, Md. Shifatul Ahsan Fighting depression: psychological approaches among Bangladeshi university students
description	This thesis is submitted in partial fulfillment of the requirements for the degree of Bachelor of Science in Computer Science, 2022.
author2	Anwar, Md. Tawhid
author_facet	Anwar, Md. Tawhid Sen, Sanjib Kumar Apurba, Md. Shifatul Ahsan
format	Thesis
author	Sen, Sanjib Kumar Apurba, Md. Shifatul Ahsan
author_sort	Sen, Sanjib Kumar
title	Fighting depression: psychological approaches among Bangladeshi university students
title_short	Fighting depression: psychological approaches among Bangladeshi university students
title_full	Fighting depression: psychological approaches among Bangladeshi university students
title_fullStr	Fighting depression: psychological approaches among Bangladeshi university students
title_full_unstemmed	Fighting depression: psychological approaches among Bangladeshi university students
title_sort	fighting depression: psychological approaches among bangladeshi university students
publisher	Brac University
publishDate	2022
url	http://hdl.handle.net/10361/17137
work_keys_str_mv	AT sensanjibkumar fightingdepressionpsychologicalapproachesamongbangladeshiuniversitystudents AT apurbamdshifatulahsan fightingdepressionpsychologicalapproachesamongbangladeshiuniversitystudents
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Fighting depression: psychological approaches among Bangladeshi university students

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