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Applications of large language models in psychiatry: a systematic review.
Omar, Mahmud; Soffer, Shelly; Charney, Alexander W; Landi, Isotta; Nadkarni, Girish N; Klang, Eyal.
Affiliation
  • Omar M; Faculty of Medicine, Tel-Aviv University, Tel-Aviv, Israel.
  • Soffer S; Internal Medicine B, Assuta Medical Center, Ashdod, Israel.
  • Charney AW; Ben-Gurion University of the Negev, Be'er Sheva, Israel.
  • Landi I; Icahn School of Medicine at Mount Sinai, New York, NY, United States.
  • Nadkarni GN; Icahn School of Medicine at Mount Sinai, New York, NY, United States.
  • Klang E; Hasso Plattner Institute for Digital Health at Mount Sinai, Icahn School of Medicine at Mount Sinai, New York, NY, United States.
Front Psychiatry ; 15: 1422807, 2024.
Article in En | MEDLINE | ID: mdl-38979501
ABSTRACT

Background:

With their unmatched ability to interpret and engage with human language and context, large language models (LLMs) hint at the potential to bridge AI and human cognitive processes. This review explores the current application of LLMs, such as ChatGPT, in the field of psychiatry.

Methods:

We followed PRISMA guidelines and searched through PubMed, Embase, Web of Science, and Scopus, up until March 2024.

Results:

From 771 retrieved articles, we included 16 that directly examine LLMs' use in psychiatry. LLMs, particularly ChatGPT and GPT-4, showed diverse applications in clinical reasoning, social media, and education within psychiatry. They can assist in diagnosing mental health issues, managing depression, evaluating suicide risk, and supporting education in the field. However, our review also points out their limitations, such as difficulties with complex cases and potential underestimation of suicide risks.

Conclusion:

Early research in psychiatry reveals LLMs' versatile applications, from diagnostic support to educational roles. Given the rapid pace of advancement, future investigations are poised to explore the extent to which these models might redefine traditional roles in mental health care.
Key words

Full text: 1 Collection: 01-internacional Database: MEDLINE Language: En Journal: Front Psychiatry Year: 2024 Document type: Article Affiliation country:

Full text: 1 Collection: 01-internacional Database: MEDLINE Language: En Journal: Front Psychiatry Year: 2024 Document type: Article Affiliation country: