The future landscape of large language models in medicine

Будущий ландшафт больших языковых моделей в медицине
Jakob Nikolas Kather, Hannah Sophie Muti, Jan Clusmann, Narmin Ghaffari Laleh, Fiona R. Kolbinger, Gregory Patrick Veldhuizen, Jan‐Niklas Eckardt, Zunamys I. Carrero, Chiara Maria Lavinia Löffler, Sophie-Caroline Schwarzkopf, Michaela Unger, Sophia J. Wagner
2023-10-10

ChatGPTclinical practicelarge language modelsmedical educationmedical research
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.
1
Because of limited accountability and transparency, LLMs may also disseminate misinformation and exacerbate scientific misconduct.
2
Interactive LLMs such as ChatGPT have potential applications across clinical practice, medical research, and medical education.
3
LLMs could democratize medical knowledge and improve access to healthcare.
4
Large language models can answer questions, summarize, paraphrase, and translate text at a level nearly indistinguishable from human capabilities.
5
The article systematically reviews the potential benefits and limitations of LLMs across major medical domains.

large language models (LLMs) in medicine

the potentials and limitations of LLMs in clinical practice, medical research, and medical education, including their effects on healthcare access, misinformation, accountability, transparency, and scientific misconduct

Publication Details
Publication Date
2023-10-10
Journal
Publisher
ISSN
Cited by
1045
Access Type
Author Information
Authors
Jakob Nikolas Kather
Hannah Sophie Muti
Jan Clusmann
Narmin Ghaffari Laleh
Fiona R. Kolbinger
Gregory Patrick Veldhuizen
Jan‐Niklas Eckardt
Zunamys I. Carrero
Chiara Maria Lavinia Löffler
Sophie-Caroline Schwarzkopf
Michaela Unger
Sophia J. Wagner
Explore further
Open the scid.ai AI chat with a ready-made request: it will find papers on a similar topic and help build a literature review.
Find similar papers in the chat →
Make a presentation
100%