Integration and Assessment of ChatGPT in Medical Case Reporting: A Multifaceted Approach

Kuan Chen Lin, Tsung An Chen, Ming Hwai Lin, Yu Chun Chen*, Tzeng-Ji Chen*

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

Abstract

ChatGPT, a large language model, has gained significance in medical writing, particularly in case reports that document the course of an illness. This article explores the integration of ChatGPT and how ChatGPT shapes the process, product, and politics of medical writing in the real world. We conducted a bibliometric analysis on case reports utilizing ChatGPT and indexed in PubMed, encompassing publication information. Furthermore, an in-depth analysis was conducted to categorize the applications and limitations of ChatGPT and the publication trend of application categories. A total of 66 case reports utilizing ChatGPT were identified, with a predominant preference for the online version and English input by the authors. The prevalent application categories were information retrieval and content generation. Notably, this trend remained consistent across different months. Within the subset of 32 articles addressing ChatGPT limitations in case report writing, concerns related to inaccuracies and a lack of clinical context were prominently emphasized. This pointed out the important role of clinical thinking and professional expertise, representing the foundational tenets of medical education, while also accentuating the distinction between physicians and generative artificial intelligence.

Original languageEnglish
Pages (from-to)888-901
Number of pages14
JournalEuropean Journal of Investigation in Health, Psychology and Education
Volume14
Issue number4
DOIs
StatePublished - Apr 2024

Keywords

  • artificial intelligence
  • case reports
  • clinical thinking
  • health science
  • LLM
  • medical writing

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