Assessing the Readability of Patient Education Materials on Cardiac Catheterization From Artificial Intelligence Chatbots: An Observational Cross-Sectional Study.

Journal: Cureus
Published Date: Jul 4, 2024

Abstract

BACKGROUND: Artificial intelligence (AI) is a burgeoning new field that has increased in popularity over the past couple of years, coinciding with the public release of large language model (LLM)-driven chatbots. These chatbots, such as ChatGPT, can be engaged directly in conversation, allowing users to ask them questions or issue other commands. Since LLMs are trained on large amounts of text data, they can also answer questions reliably and factually, an ability that has allowed them to serve as a source for medical inquiries. This study seeks to assess the readability of patient education materials on cardiac catheterization across four of the most common chatbots: ChatGPT, Microsoft Copilot, Google Gemini, and Meta AI.

Authors

  • Benjamin J Behers
    Florida State University Internal Medicine Residency, Sarasota Memorial Hospital, Sarasota, FL.
  • Ian A Vargas
    Department of Internal Medicine, Sarasota Memorial Hospital, Sarasota, USA.
  • Brett M Behers
    University of South Florida College of Medicine, Tampa, FL.
  • Manuel A Rosario
    Florida State University Internal Medicine Residency, Sarasota Memorial Hospital, Sarasota, FL.
  • Caroline N Wojtas
    Florida State University Internal Medicine Residency, Sarasota Memorial Hospital, Sarasota, FL.
  • Alexander C Deevers
    Department of Clinical Research, University of Florida, Gainesville, USA.
  • Karen M Hamad
    Florida State University Internal Medicine Residency, Sarasota Memorial Hospital, Sarasota, FL.

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