Transforming mental health with DeepSeek

Mental health disorders pose a significant global health challenge, affecting one in eight individuals, yet access to effective care remains hindered by professional shortages, stigma, and cultural barriers. This chapter explores the integration of large language models (LLMs), with a particular focus on DeepSeek, into the field of mental health care. It reviews the growing potential of generative AI to address long-standing challenges such as limited access, stigma, and resource constraints. The chapter discusses DeepSeek’s applications, and unique features including multilingual support, empathetic interaction, and transparent reasoning, across key areas such as early detection, digital triage, clinical decision support, and patient engagement. Real-world studies and comparative benchmarks highlight DeepSeek’s strengths and current limitations. The chapter also examines ethical, practical, and technical challenges, including issues of bias, explainability, and clinical safety. It concludes by emphasising the need for ongoing research, human oversight, and multidisciplinary collaboration to ensure that DeepSeek lead to more accessible, effective, and equitable mental health care.