The future landscape of large language models in medicine
Research output: Contribution to journal › Review article › Contributed › peer-review
Contributors
Abstract
Large language models (LLMs) are artificial intelligence (AI) tools specifically trained to process and generate text. LLMs attracted substantial public attention after OpenAI's ChatGPT was made publicly available in November 2022. LLMs can often answer questions, summarize, paraphrase and translate text on a level that is nearly indistinguishable from human capabilities. The possibility to actively interact with models like ChatGPT makes LLMs attractive tools in various fields, including medicine. While these models have the potential to democratize medical knowledge and facilitate access to healthcare, they could equally distribute misinformation and exacerbate scientific misconduct due to a lack of accountability and transparency. In this article, we provide a systematic and comprehensive overview of the potentials and limitations of LLMs in clinical practice, medical research and medical education.
Details
Original language | English |
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Article number | 141 |
Number of pages | 8 |
Journal | Communications medicine |
Volume | 3 |
Issue number | 1 |
Publication status | Published - 10 Oct 2023 |
Peer-reviewed | Yes |
External IDs
PubMedCentral | PMC10564921 |
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WOS | 001078603900001 |
unpaywall | 10.1038/s43856-023-00370-1 |
ORCID | /0000-0003-2265-4809/work/149798321 |
ORCID | /0000-0001-8501-1566/work/150883651 |
Scopus | 85204247190 |
Keywords
Sustainable Development Goals
Keywords
- Care, Communication, Impact, Patient safety