AI – Powered Depression Prediction

• Author(s): Sharmila P.; Sarathi R; Siva Prasanth B; Theppan TK; Udaya Bharaathi K; Vishal Raj N D
• Paper ID: 1717090
• Page: 3811-3821
• Published Date: 01-05-2026
• Published In: Iconic Research And Engineering Journals
• Publisher: IRE Journals
• e-ISSN: 2456-8880
• Volume/Issue: Volume 9 Issue 10 April-2026
• DOI: https://doi.org/10.64388/IREV9I10-1717090

Abstract

The proposed is a sophisticated web-based platform designed to leverage artificial intelligence for the early detection and monitoring of depressive disorders. It integrates multiple analytical modules, including linguistic sentiment analysis, facial expression recognition, and vocal biomarker tracking, along with a clinical referral portal for professional intervention. The system enables users to input symptoms, undergo digital assessments, receive risk probability scores, and upload video journals to ensure accuracy in mental health monitoring. Additionally, the clinical module allows practitioners to access patient insights with data visualizations and longitudinal reports directly through the website. Developed using Python, React, and TensorFlow, the platform emphasizes data privacy, real-time processing, and empathetic user interaction, offering a professional, reliable, and accessible solution for modern psychiatric Artificial Intelligence, Depression Detection, Sentiment Analysis, Mental Health, Machine Learning Portal, Predictive Modelling, User Experience, Python, React, TensorFlow.

Citations

IRE Journals:
Sharmila P., Sarathi R, Siva Prasanth B, Theppan TK, Udaya Bharaathi K; Vishal Raj N D "AI – Powered Depression Prediction" Iconic Research And Engineering Journals Volume 9 Issue 10 2026 Page 3811-3821 https://doi.org/10.64388/IREV9I10-1717090

IEEE:
Sharmila P., Sarathi R, Siva Prasanth B, Theppan TK, Udaya Bharaathi K; Vishal Raj N D "AI – Powered Depression Prediction" Iconic Research And Engineering Journals, vol. 9, no. 10, Apr. 2026, doi: https://doi.org/10.64388/IREV9I10-1717090

APA:
Sharmila P., Sarathi R, Siva Prasanth B, Theppan TK, Udaya Bharaathi K; Vishal Raj N D (2026). AI – Powered Depression Prediction. Iconic Research And Engineering Journals, 9(10). doi: https://doi.org/10.64388/IREV9I10-1717090

MLA:
Sharmila P., Sarathi R, Siva Prasanth B, Theppan TK, Udaya Bharaathi K; Vishal Raj N D "AI – Powered Depression Prediction" Iconic Research And Engineering Journals, vol. 9, no. 10, Apr. 2026. Crossref, https://doi.org/10.64388/IREV9I10-1717090

BibTeX

@article{1717090,
author = {Sharmila P., Sarathi R, Siva Prasanth B, Theppan TK, Udaya Bharaathi K; Vishal Raj N D},
title = {AI – Powered Depression Prediction},
journal = {Iconic Research And Engineering Journals},
year = {2026},
volume = {9},
number = {10},
pages = {3811-3821},
issn = {2456-8880},
url = {https://www.irejournals.com/formatedpaper/1717090.pdf},
abstract = {The proposed is a sophisticated web-based platform designed to leverage artificial intelligence for the early detection and monitoring of depressive disorders. It integrates multiple analytical modules, including linguistic sentiment analysis, facial expression recognition, and vocal biomarker tracking, along with a clinical referral portal for professional intervention. The system enables users to input symptoms, undergo digital assessments, receive risk probability scores, and upload video journals to ensure accuracy in mental health monitoring. Additionally, the clinical module allows practitioners to access patient insights with data visualizations and longitudinal reports directly through the website. Developed using Python, React, and TensorFlow, the platform emphasizes data privacy, real-time processing, and empathetic user interaction, offering a professional, reliable, and accessible solution for modern psychiatric Artificial Intelligence, Depression Detection, Sentiment Analysis, Mental Health, Machine Learning Portal, Predictive Modelling, User Experience, Python, React, TensorFlow.},
month = {April}
}