Analysis of mental health conditions such as depression, anxiety and stress using machine learning algorithm

Analysis of mental health conditions such as depression, anxiety and stress using machine learning algorithm

Registration ID: IJNRD_211126

Published ID: IJNRD2312244

DOI: Click Here to Get

Shreya Vats , Manmeet Singh , Khushi Mishra , Kalash Jain , Dr. Ankit Verma

- Mental Health, Mental Health Analysis Disorder, Anxiety, Depression, Stress, F1 score, Machine Learning Algorithms.

This review paper examines the role of machine learning algorithms in predicting and differentiating mental health conditions, specifically depression, anxiety, and stress. Traditional diagnostic approaches face limitations in subjectivity and resource constraints, prompting the exploration of machine learning as a tool for early detection and intervention. Following the PRISMA protocol, our methodology involves meticulous source identification from authoritative journals and conferences, repository selection from reputable publishers, and strategic queries to navigate vast information. The performance assessment phase scrutinizes the efficacy of machine learning approaches in diagnosing mental health problems. Results from prominent research papers demonstrate the application of various machine learning algorithms, including tree-based models, artificial neural networks, random forests, support vector machines, CatBoost, and XGBoost. This review contributes to the ongoing effort to enhance mental health diagnosis, treatment, and intervention, emphasizing the significance of machine learning advancements in addressing global mental health challenges.

Published Paper   E-Certificate

"Analysis of mental health conditions such as depression, anxiety and stress using machine learning algorithm", IJNRD - INTERNATIONAL JOURNAL OF NOVEL RESEARCH AND DEVELOPMENT (www.IJNRD.org), ISSN:2456-4184, Vol.8, Issue 12, page no.c406-c415, December-2023, Available :https://ijnrd.org/papers/IJNRD2312244.pdf

Volume 8 Issue 12, December-2023

Pages : c406-c415

Paper Reg. ID: IJNRD_211126

Published Paper Id: IJNRD2312244

Downloads: 000121229

Research Area: Computer Science & Technology 

Country: Delhi, Delhi, India

Published Paper PDF: https://ijnrd.org/papers/IJNRD2312244.pdf

Published Paper URL: https://ijnrd.org/viewpaperforall?paper=IJNRD2312244

Journal Name: INTERNATIONAL JOURNAL OF NOVEL RESEARCH AND DEVELOPMENT(IJNRD)

ISSN: 2456-4184 | IMPACT FACTOR: 8.76 Calculated By Google Scholar | ESTD YEAR: 2016

An International Scholarly Open Access Journal, Peer-Reviewed, Refereed Journal Impact Factor 8.76 Calculate by Google Scholar and Semantic Scholar | AI-Powered Research Tool, Multidisciplinary, Monthly, Multilanguage Journal Indexing in All Major Database & Metadata, Citation Generator

Publisher: IJNRD (IJ Publication) Janvi Wave

This work is licensed under a Creative Commons Attribution 4.0 International License and The Open Definition

Call For Paper - Volume 10 | Issue 8 | August 2025

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INTERNATIONAL JOURNAL OF NOVEL RESEARCH AND DEVELOPMENT (IJNRD) aims to explore advances in research pertaining to applied, theoretical and experimental Technological studies. The goal is to promote scientific information interchange between researchers, developers, engineers, students, and practitioners working in and around the world. IJNRD will provide an opportunity for practitioners and educators of engineering field to exchange research evidence, models of best practice and innovative ideas.

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