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Large language models in radiology: fundamentals, applications, ethical considerations, risks, and future directions

Akinci D'Antonoli, Tugba; Stanzione, Arnaldo; Bluethgen, Christian; Vernuccio, Federica; Ugga, Lorenzo; Klontzas, Michail E; Cuocolo, Renato; Cannella, Roberto; Koçak, Burak (2024). Large language models in radiology: fundamentals, applications, ethical considerations, risks, and future directions. Diagnostic and Interventional Radiology, 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.

Additional indexing

Item Type:Journal Article, refereed, further contribution
Communities & Collections:04 Faculty of Medicine > University Hospital Zurich > Clinic for Diagnostic and Interventional Radiology
Dewey Decimal Classification:610 Medicine & health
Uncontrolled Keywords:ChatGPT; Large language models; artificial intelligence; deep learning; natural language processing
Language:English
Date:1 March 2024
Deposited On:12 Dec 2023 08:21
Last Modified:30 Aug 2024 01:38
Publisher:Turkish Society of Radiology
ISSN:1305-3825
OA Status:Gold
Free access at:Publisher DOI. An embargo period may apply.
Publisher DOI:https://doi.org/10.4274/dir.2023.232417
PubMed ID:37789676
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  • Language: English
  • Licence: Creative Commons: Attribution-NonCommercial 4.0 International (CC BY-NC 4.0)

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