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

• Published in: Diagnostic and interventional radiology (Ankara, Turkey) Vol. 30; no. 2; pp. 80 - 90
• Main Authors: Akinci D'Antonoli, Tugba, Stanzione, Arnaldo, Bluethgen, Christian, Vernuccio, Federica, Ugga, Lorenzo, Klontzas, Michail E, Cuocolo, Renato, Cannella, Roberto, Koçak, Burak
• Format: Journal Article
• Language: English
• Published: Turkey Galenos Publishing 01.03.2024; Galenos Publishing House
• Subjects: Artificial Intelligence; Artificial Intelligence and Informatics - Review; chatgpt; deep learning; Humans; Language; large language models; natural language processing; Radiography; Radiologists; Radiology; deep learning; Large language models; natural language processing; ChatGPT; artificial intelligence
• ISSN: 1305-3825; 1305-3612
• DOI: 10.4274/dir.2023.232417

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.