• Ms. Deepika Kirti
• Dr. Ruchi Sawhney
• Ms. Swati Sharma
• Dr. Sanjay Kumar Singh

Depression is a mental health disorder that can have a significant impact on people's daily lives. It is a major problem in today's society and can cause a loss of interest in common activities, leading to suicidal thoughts. To detect depression, researchers have been exploring different methods to effectively identify it. There is a pressing need for an automated system to help detect depression in different age groups. Several studies have been proposed on this topic, and this study aims to analyze project based on machine learning (ML) techniques used to detect depression. The purpose of this article is to provide an overview of various ML techniques used to identify and analyze emotions and, consequently, depression. By investigating the different approaches to detecting depression, this study contributes to a better understanding of the relationship between depression and human emotions. In turn, this knowledge can help develop more effective methods to detect depression, ultimately improving people's mental health and quality of life.

Machine Learning, WHO, GAD, PHQ, ML Algorithm

"Questionnaire Based Depression Detection System using Machine Learning", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.11, Issue 5, page no.c1-c5, May-2024, Available :http://www.jetir.org/papers/JETIR2405201.pdf

"Questionnaire Based Depression Detection System using Machine Learning", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.11, Issue 5, page no. ppc1-c5, May-2024, Available at : http://www.jetir.org/papers/JETIR2405201.pdf