Analysis of ChatGPT publications in radiology: Literature so far.

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  • Additional Information
    • Source:
      Publisher: Mosby Country of Publication: United States NLM ID: 7607123 Publication Model: Print-Electronic Cited Medium: Internet ISSN: 1535-6302 (Electronic) Linking ISSN: 03630188 NLM ISO Abbreviation: Curr Probl Diagn Radiol Subsets: MEDLINE
    • Publication Information:
      Publication: St. Louis : Mosby
      Original Publication: Chicago, Year Book Medical Publishers.
    • Subject Terms:
      Publications* ; Radiology* ; Artificial Intelligence*; Diagnostic Imaging ; Radiography
    • Abstract:
      Objective: To perform a detailed qualitative and quantitative analysis of the published literature on ChatGPT and radiology in the nine months since its public release, detailing the scope of the work in the short timeframe.
      Methods: A systematic literature search was carried out of the MEDLINE, EMBASE databases through August 15, 2023 for articles that were focused on ChatGPT and imaging/radiology. Articles were classified into original research and reviews/perspectives. Quantitative analysis was carried out by two experienced radiologists using objective scoring systems for evaluating original and non-original research.
      Results: 51 articles were published involving ChatGPT and radiology/imaging dating from 26 Jan 2023 to the last article published on 14 Aug 2023. 23 articles were original research while the rest included reviews/perspectives or brief communications. For quantitative analysis scored by two readers, we included 23 original research and 17 non-original research articles (after excluding 11 letters as responses to previous articles). Mean score for original research was 3.20 out of 5 (across five questions), while mean score for non-original research was 1.17 out of 2 (across six questions). Mean score grading performance of ChatGPT in original research was 3.20 out of five (across two questions).
      Discussion: While it is early days for ChatGPT and its impact in radiology, there has already been a plethora of articles talking about the multifaceted nature of the tool and how it can impact every aspect of radiology from patient education, pre-authorization, protocol selection, generating differentials, to structuring radiology reports. Most articles show impressive performance of ChatGPT which can only improve with more research and improvements in the tool itself. There have also been several articles which have highlighted the limitations of ChatGPT in its current iteration, which will allow radiologists and researchers to improve these areas.
      (Copyright © 2023. Published by Elsevier Inc.)
    • Publication Date:
      Date Created: 20231027 Date Completed: 20240305 Latest Revision: 20240312
    • Publication Date:
      20240313
    • Accession Number:
      10.1067/j.cpradiol.2023.10.013
    • Accession Number:
      37891083