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Area of Science:

  • Artificial Intelligence
  • Medical Informatics
  • Clinical Decision Support

Background:

  • Artificial intelligence (AI) text generators, such as ChatGPT, are increasingly capable of answering questions.
  • However, their performance in responding to complex medical queries remains uncertain.

Purpose of the Study:

  • To evaluate the accuracy and reliability of ChatGPT when answering a complex clinical question.
  • Assessing the veracity of AI-generated medical information is crucial.

Main Methods:

  • A clinical question was formulated using the Population, Intervention, Comparison, Outcome, and Time (PICOT) framework.
  • ChatGPT's response and cited references were critically reviewed against full-text articles to verify accuracy.

Main Results:

  • ChatGPT failed to provide a verifiable answer to the PICOT question.
  • Cited references contained inaccurate journal details, and summarized study information, including fabricated data, was found to be false.

Conclusions:

  • ChatGPT can generate seemingly legitimate but factually incorrect responses.
  • The lack of transparency in data sourcing and tendency to fabricate plausible information render ChatGPT an unreliable tool for clinical applications.