Preprint Review Version 1 Preserved in Portico This version is not peer-reviewed

ChatGPT Goes to The Radiology Department: A Pictorial Review

Version 1 : Received: 8 December 2023 / Approved: 11 December 2023 / Online: 11 December 2023 (14:37:17 CET)

How to cite: Zanon, C.; Toniolo, A.; Bini, C.; Quaia, E. ChatGPT Goes to The Radiology Department: A Pictorial Review. Preprints 2023, 2023120714. https://doi.org/10.20944/preprints202312.0714.v1 Zanon, C.; Toniolo, A.; Bini, C.; Quaia, E. ChatGPT Goes to The Radiology Department: A Pictorial Review. Preprints 2023, 2023120714. https://doi.org/10.20944/preprints202312.0714.v1

Abstract

Artificial intelligence (AI) tools, such as OpenAI's Chat Generative Pre-trained Transformer (ChatGPT), have great potential in various fields, such as healthcare, education, and industry. This review highlights the applications and challenges of the ChatGPT versions 3.5 and 4.0 in radiology. ChatGPT can process medical texts, analyze medical images, and generate reports and summaries for different audiences. ChatGPT can also answer patients' questions and translate complex medical information into a plain language. ChatGPT has shown impressive results in medical tests and quizzes, indicating its potential to enhance diagnostic accuracy and medical education. These models show promise for reducing diagnosis times and healthcare costs. However, ChatGPT also faces challenges and limitations, such as a lack of visual content, ethical and legal issues, data quality, and error detection. This review highlights the benefits and future directions of ChatGPT and artificial intelligence (AI) in radiology.

Keywords

ChatGPT; radiology; diagnostic accuracy; natural language processing; artificial intelligence

Subject

Medicine and Pharmacology, Other

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