Leveraging AI for the Diagnosis and Management of Mental Health Disorders: Opportunities and Challenges

DOI

10.2991/978-94-6239-756-9_24How to use a DOI?

Keywords

Artificial Intelligence; Mental Health; Multimodal Deep Learning; Early Diagnosis; Ethical AI

Abstract

Mental health problems such as depression, anxiety, schizophrenia, and Alzheimer’s disease continue to present significant challenges due to their delayed detection, lack of clinical resources, and subjective diagnosis methods. Detection of these diseases in their early stages becomes very crucial for clinicians to advise them with the treatments. But with clinical tests it becomes very difficult to identify them at early stages. By introducing AI in detection of mental health disorders, it gives a path to early detection. Rather than using single modality to screening, diagnosis by investigating multiple modalities gives promising results. This research aims to investigate the possible advantages of multimodal data integration for the early diagnosis, screening, and continuous monitoring of mental health disorders using artificial intelligence. The literature review includes peer-reviewed articles on digital phenotyping, machine learning, deep learning, natural language processing, neuroimaging, and voice analysis. The findings of this research show that AI models are 10-15% more accurate than traditional methods for the diagnosis of cognitive decline from behavioral and sensor data, schizophrenia from MRI scans, and depression from voice characteristics.

Copyright

© 2026 The Author(s)

Open Access

Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial 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 license and indicate if changes were made.

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TY  - CONF
AU  - Manisha Patil
AU  - Geetanjali Sharma
AU  - Rahee Walambe
PY  - 2026
DA  - 2026/08/31
TI  - Leveraging AI for the Diagnosis and Management of Mental Health Disorders: Opportunities and Challenges
BT  - Proceedings of the Conference on Bioengineering for Global Health (SYMRESEARCH 2.0 2025)
PB  - Atlantis Press
SP  - 342
EP  - 358
SN  - 2468-5747
UR  - https://doi.org/10.2991/978-94-6239-756-9_24
DO  - 10.2991/978-94-6239-756-9_24
ID  - Patil2026
ER  -