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Advances in Artificial Intelligence-Based Depression Diagnosis: A Systematic Review
Review Article | Published: 27 August 2025
ICCK Transactions on Emerging Topics in Artificial Intelligence Volume 2, Issue 3, 2025: 148-156
Volume 2, Issue 3, ICCK Transactions on Emerging Topics in Artificial Intelligence
Volume 2, Issue 3, 2025
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ICCK Transactions on Emerging Topics in Artificial Intelligence, Volume 2, Issue 3, 2025: 148-156

Open Access | Review Article | 27 August 2025
Advances in Artificial Intelligence-Based Depression Diagnosis: A Systematic Review
by
Liangguo Wang Liangguo Wang 1
Jiaqian Wu Jiaqian Wu 2 *
1 Xinjiang Hetian College, Xinjiang 848000, China
2 Beijing Anding Hospital, Capital Medical University, Beijing 100088, China
* Corresponding Author: Jiaqian Wu, [email protected]
DOI: 10.62762/TETAI.2025.416797
Received: 22 May 2025, Accepted: 18 July 2025, Published: 27 August 2025  
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Abstract
This study systematically reviews the current status and recent advances in intelligent depression detection, aiming to provide insights for applying artificial intelligence in mental health. Using a systematic review approach, we analyze detection methods based on multiple data types including voice, facial expressions, body signals, and social media texts, while examining how algorithms have evolved from traditional machine learning to deep learning. Results show that AI technology has clear benefits in improving detection accuracy, reducing costs, and enabling early warning systems. Current research still faces important challenges in data collection, technical reliability, clinical use, and privacy concerns. Future work should focus on combining knowledge from different fields, implementing systems in clinical practice, and developing standards for wider adoption.
Keywords
depression
artificial intelligence
multimodal features
deep learning
intelligent detection
Data Availability Statement
Not applicable.
Funding
This work was supported by the Key Project of Natural Science Foundation of Xinjiang Hetian College under Grant 2025ZR002.
Conflicts of Interest
The authors declare no conflicts of interest.
Ethical Approval and Consent to Participate
Not applicable.
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Cite This Article
APA Style
Wang, L., & Wu, J. (2025). Advances in Artificial Intelligence-Based Depression Diagnosis: A Systematic Review. ICCK Transactions on Emerging Topics in Artificial Intelligence, 2(3), 148–156. https://doi.org/10.62762/TETAI.2025.416797
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CC BY Copyright © 2025 by the Author(s). Published by Institute of Central Computation and Knowledge. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/), which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made.
ICCK Transactions on Emerging Topics in Artificial Intelligence

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