Semantic Scholar Open Access 2023 843 sitasi

The future landscape of large language models in medicine

J. Clusmann F. Kolbinger H. Muti Zunamys I. Carrero Jan-Niklas Eckardt +7 lainnya

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Abstrak

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.

Topik & Kata Kunci

Medicine

Penulis (12)

J. Clusmann

F. Kolbinger

H. Muti

Zunamys I. Carrero

Jan-Niklas Eckardt

Narmin Ghaffari Laleh

C. Löffler

Sophie-Caroline Schwarzkopf

Michaela Unger

G. P. Veldhuizen

Sophia J Wagner

Jakob Nikolas Kather

Format Sitasi

APA MLA BibTeX

Clusmann, J., Kolbinger, F., Muti, H., Carrero, Z.I., Eckardt, J., Laleh, N.G. et al. (2023). The future landscape of large language models in medicine. https://doi.org/10.1038/s43856-023-00370-1

Akses Cepat

Lihat di Sumber doi.org/10.1038/s43856-023-00370-1

Informasi Jurnal

Tahun Terbit: 2023
Bahasa: en
Total Sitasi: 843×
Sumber Database: Semantic Scholar
DOI: 10.1038/s43856-023-00370-1
Akses: Open Access ✓