Generative artificial intelligence in depression research: A bibliometric analysis of WoSCC-Indexed literature - Takeaways - MDSpire

Generative artificial intelligence in depression research: A bibliometric analysis of WoSCC-Indexed literature

  • By

  • Hongfei Chen

  • Lin Chen

  • Jin Yang

  • Aifa Tang

  • Yafei Yang

  • May 25, 2026

  • 0 min

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  • 1

    Depression affects over 280 million people globally and is a leading cause of disability and reduced quality of life.

  • 2

    The COVID-19 pandemic has exacerbated the prevalence of depressive and anxiety disorders, highlighting urgent mental health research needs.

  • 3

    Generative AI, particularly large language models, offers innovative approaches for early detection and treatment of depression.

  • 4

    This study conducts a bibliometric analysis of literature on generative AI in depression from 2023 to 2025, mapping research trends and contributions.

  • 5

    The analysis aims to identify knowledge gaps and inform future development and governance of generative AI applications in depression.

Original Source(s)

Generative artificial intelligence in depression research: A bibliometric analysis of WoSCC-Indexed literature

  • by Hongfei Chen, Lin Chen, Jin Yang, Aifa Tang, Yafei Yang

  • May 25, 2026

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