Large language models in radiology: fundamentals, applications, ethical considerations, risks, and future directions
Authors:
- Tugba Akinci D’aNtonoliTDTugba Akinci D’aNtonoli
- Arnaldo StanzioneArnaldo Stanzione
- Christian BluethgenCBChristian Bluethgen
- Federica VernuccioFederica Vernuccio
- Lorenzo UggaLorenzo Ugga
- Michail E. KlontzasMichail E. Klontzas
- Renato CuocoloRenato Cuocolo
- Roberto CannellaRoberto Cannella
- Burak KoçakBKBurak Koçak
Top Cited Papers
Open Access
- 1 March 2024
- journal article
- review article
- Published by Galenos Yayinevi in Diagnostic and Interventional Radiology
- Vol. 30 (2) , 80-90
Abstract
With the advent of large language models (LLMs), the artificial intelligence revolution in medicine and radiology is now more tangible than ever. Every day, an increasingly large number of articles are published that utilize LLMs in radiology. To adopt and safely implement this new technology in the field, radiologists should be familiar with its key concepts, understand at least the technical basics, and be aware of the potential risks and ethical considerations that come with it. In this review article, the authors provide an overview of the LLMs that might be relevant to the radiology community and include a brief discussion of their short history, technical basics, ChatGPT, prompt engineering, potential applications in medicine and radiology, advantages, disadvantages and risks, ethical and regulatory considerations, and future directions.Keywords
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