Revolutionizing radiology with GPT-based models: Current applications, future possibilities and limitations of ChatGPT
- PMID: 36858933
- DOI: 10.1016/j.diii.2023.02.003
Revolutionizing radiology with GPT-based models: Current applications, future possibilities and limitations of ChatGPT
Abstract
Artificial intelligence has demonstrated utility and is increasingly being used in the field of radiology. The use of generative pre-trained transformer (GPT)-based models has the potential to revolutionize the field of radiology, offering new possibilities for improving accuracy, efficiency, and patient outcome. Current applications of GPT-based models in radiology include report generation, educational support, clinical decision support, patient communication, and data analysis. As these models continue to advance and improve, it is likely that more innovative uses for GPT-based models in the field of radiology at large will be developed, further enhancing the role of technology in the diagnostic process. ChatGPT is a variant of GPT that is specifically fine-tuned for conversational language understanding and generation. This article reports some answers provided by ChatGPT to various questions that radiologists may have regarding ChatGPT and identifies the potential benefits ChatGPT may offer in their daily practice but also current limitations. Similar to other applications of artificial intelligence in the field of imaging, further formal validation of ChatGPT is required.
Keywords: Artificial intelligence; ChatGPT; Generative pre-trained transformer (GPT); Radiology.
Copyright © 2023 Société française de radiologie. Published by Elsevier Masson SAS. All rights reserved.
Conflict of interest statement
Disclosure of interest Philippe Soyer is the Editor-in-Chief of Diagnostic & Interventional Imaging. The other authors have no conflicts of interest to declare.
Comment in
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Beyond chatting: The opportunities and challenges of ChatGPT in medicine and radiology.Diagn Interv Imaging. 2023 Jun;104(6):263-264. doi: 10.1016/j.diii.2023.02.006. Epub 2023 Mar 14. Diagn Interv Imaging. 2023. PMID: 36925365 No abstract available.
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