Large Language Models in Mental Health: A Systematic Review of Applications, Innovations, and Ethical Challenges
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Abstract
This review explores the applications of large language models in mental health, focusing on their use in early detection of mental health issues and the ethical challenges involved.
Reality Card
The review integrates interdisciplinary findings to demonstrate how LLMs can enhance early detection of mental health issues and support personalized therapy.
Emerging multimodal fusion techniques integrating text, speech, and sensor data for improved mental health diagnosis and monitoring.
Ongoing ethical, sociotechnical, and regulatory challenges may hinder the safe deployment of LLMs in real-world mental health care.
Paper to code
Verified implementation resources so builders can test the paper’s claims instead of stopping at the abstract.