Assessing the accuracy and quality of artificial intelligence (AI) chatbot-generated responses in making patient-specific drug-therapy and healthcare-related decisions.

Journal: BMC medical informatics and decision making
PMID: 39719573

Abstract

BACKGROUND: Interactive artificial intelligence tools such as ChatGPT have gained popularity, yet little is known about their reliability as a reference tool for healthcare-related information for healthcare providers and trainees. The objective of this study was to assess the consistency, quality, and accuracy of the responses generated by ChatGPT on healthcare-related inquiries.

Authors

  • Meron W Shiferaw
    School of Pharmacy, University of Washington, 1959 NE Pacific Street, Box 357630, Seattle, WA, 98195, USA.
  • Taylor Zheng
    School of Pharmacy, University of Washington, 1959 NE Pacific Street, Box 357630, Seattle, WA, 98195, USA.
  • Abigail Winter
    School of Pharmacy, University of Washington, 1959 NE Pacific Street, Box 357630, Seattle, WA, 98195, USA.
  • Leigh Ann Mike
    School of Pharmacy, University of Washington, 1959 NE Pacific Street, Box 357630, Seattle, WA, 98195, USA.
  • Lingtak-Neander Chan
    School of Pharmacy, University of Washington, 1959 NE Pacific Street, Box 357630, Seattle, WA, 98195, USA. neander@uw.edu.

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