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ISSN Approved Journal || eISSN: 2582-8185 || CODEN: IJSRO2 || Impact Factor 8.2 || Google Scholar and CrossRef Indexed

Peer Reviewed and Referred Journal || Free Certificate of Publication

Research and review articles are invited for publication in March 2026 (Volume 18, Issue 3) Submit manuscript

AI4MentalWellness: Democratizing access to mood insights and professional mental health guidance

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  • AI4MentalWellness: Democratizing access to mood insights and professional mental health guidance

Durga Bhavani Sankabathula *, Tapaswini Chinde, Gousia Rahmani Shaik and Poojitha Dommeti

Department of Computer Science and Engineering, Aditya College of Engineering and Technology, Surampalem, Kakinada, Andhra Pradesh, India.

Research Article

International Journal of Science and Research Archive, 2026, 18(03), 332–338

Article DOI: 10.30574/ijsra.2026.18.3.0451

DOI url: https://doi.org/10.30574/ijsra.2026.18.3.0451

Received on 27 January 2026; revised on 02 March 2026; accepted on 04 March 2026

AI4MentalWellness is an AI based model that aims to level access to mood knowledge and professional mental health advice through a user-friendly and free-to-use application. The system helps users to monitor the emotional states on a regular basis, note the daily experiences and discover the pattern of stresses through smart analysis tools. The platform enhances self-awareness of mental health risks and early intervention by converting self-reported data into useful mood inferences. Another impact of the application is that it offers a safe platform upon which users are able to communicate with therapists in a bid to help the professionals to comprehend emotional patterns and provide customized support. The presented structure is centered on simplicity, privacy, and constant interaction to develop positive mental health habits. It will address the issues of stigma reduction, emotional self-monitoring, and enhance access to care among individuals who do not seek help early. This study shows that mood analysis using AI can assist in preventing mental health and enhancing emotional well-being among various groups in society. AI4MentalWellness is an AI based model that aims to level access to mood knowledge and professional mental health advice through a user-friendly and free-to-use application. The system helps users to monitor the emotional states on a regular basis, note the daily experiences and discover the pattern of stresses through smart analysis tools. The platform enhances self-awareness of mental health risks and early intervention by converting self-reported data into useful mood inferences. Another impact of the application is that it offers a safe platform upon which users are able to communicate with therapists in a bid to help the professionals to comprehend emotional patterns and provide customized support. The presented structure is centered on simplicity, privacy, and constant interaction to develop positive mental health habits. It will address the issues of stigma reduction, emotional self-monitoring, and enhance access to care among individuals who do not seek help early. This study shows that mood analysis using AI can assist in preventing mental health and enhancing emotional well-being among various groups in society.

Multi-Modal Emotion Detection; Artificial Intelligence; Machine Learning; Mental Health; Emotional Well-Being; Mental Health Support; Professionals Help; Guidance and Support

https://ijsra.net/sites/default/files/fulltext_pdf/IJSRA-2026-0451.pdf

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Durga Bhavani Sankabathula, Tapaswini Chinde, Gousia Rahmani Shaik and Poojitha Dommeti. AI4MentalWellness: Democratizing access to mood insights and professional mental health guidance. International Journal of Science and Research Archive, 2026, 18(03), 332–338. Article DOI: https://doi.org/10.30574/ijsra.2026.18.3.0451.

Copyright © Author(s). All rights reserved. This article is published under the terms of the Creative Commons Attribution 4.0 International License (CC BY 4.0), which permits use, sharing, adaptation, distribution, and reproduction in any medium or format, as long as appropriate credit is given to the original author(s) and source, a link to the license is provided, and any changes made are indicated.


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