Depression Detection using Deep Learning Algorithms

Document Type : Original Article

Authors

1 Department of computer Science College of Information Technology, Misr University for Science & Technology (MUST), 6th of October City 12566 , Egypt

2 Department of Artificial intelligence , College of Information Technology, Misr University for Science & Technology (MUST), 6th of October City 12566 , Egypt

Abstract

This research study aims to provide a depression  detection project that uses text analysis and natural language 
processing (NLP) to identify symptoms of depression. In order to  conduct sentiment analysis on big datasets of tweets, this project  will employ a deep learning model. Social media platforms have  evolved into places where individuals express their ideas and  feelings. Our objective is to create a chat platform that enables  users to interact with friends, coworkers, or complete strangers  while using text analysis to identify sadness. There are several  browsers that can be used to visit the website and guidance on  interacting with it. The significance of early depression detection  and its possible effects on community well-being—including  detrimental effects on local company productivity and healthcare 
costs will be emphasized in our research. The purpose of this  project is to increase public awareness of the advantages of early  identification and to offer a deep learning-based approach to assist  people in identifying depression and obtaining the necessary  assistance

Keywords

International Integrated Intelligent Systems
Volume 1, Issue 1
February 2024
Pages 1-7

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