Academic Journal
Applications of large language models in psychiatry: a systematic review
| Title: | Applications of large language models in psychiatry: a systematic review |
|---|---|
| Authors: | Mahmud Omar, Shelly Soffer, Alexander W. Charney, Isotta Landi, Girish N. Nadkarni, Eyal Klang |
| Source: | Frontiers in Psychiatry, Vol 15 (2024) |
| Publisher Information: | Frontiers Media S.A., 2024. |
| Publication Year: | 2024 |
| Collection: | LCC:Psychiatry |
| Subject Terms: | LLMS, large language model, artificial intelligence, psychiatry, generative pre-trained transformer (GPT), Psychiatry, RC435-571 |
| More Details: | BackgroundWith 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.MethodsWe followed PRISMA guidelines and searched through PubMed, Embase, Web of Science, and Scopus, up until March 2024.ResultsFrom 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.ConclusionEarly 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. |
| Document Type: | article |
| File Description: | electronic resource |
| Language: | English |
| ISSN: | 1664-0640 |
| Relation: | https://www.frontiersin.org/articles/10.3389/fpsyt.2024.1422807/full; https://doaj.org/toc/1664-0640 |
| DOI: | 10.3389/fpsyt.2024.1422807 |
| Access URL: | https://doaj.org/article/d9e1dd773a334da983bfae6ba1f3cfd4 |
| Accession Number: | edsdoj.9e1dd773a334da983bfae6ba1f3cfd4 |
| Database: | Directory of Open Access Journals |
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