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Generative AI in Medicine and Healthcare: Promises, Opportunities and Challenges

Author

Listed:
  • Peng Zhang

    (Department of Computer Science and Data Science Institute, Vanderbilt University, Nashville, TN 37240, USA)

  • Maged N. Kamel Boulos

    (School of Medicine, University of Lisbon, 1649-028 Lisbon, Portugal)

Abstract

Generative AI (artificial intelligence) refers to algorithms and models, such as OpenAI’s ChatGPT, that can be prompted to generate various types of content. In this narrative review, we present a selection of representative examples of generative AI applications in medicine and healthcare. We then briefly discuss some associated issues, such as trust, veracity, clinical safety and reliability, privacy, copyrights, ownership, and opportunities, e.g., AI-driven conversational user interfaces for friendlier human-computer interaction. We conclude that generative AI will play an increasingly important role in medicine and healthcare as it further evolves and gets better tailored to the unique settings and requirements of the medical domain and as the laws, policies and regulatory frameworks surrounding its use start taking shape.

Suggested Citation

  • Peng Zhang & Maged N. Kamel Boulos, 2023. "Generative AI in Medicine and Healthcare: Promises, Opportunities and Challenges," Future Internet, MDPI, vol. 15(9), pages 1-15, August.
    • Handle: RePEc:gam:jftint:v:15:y:2023:i:9:p:286-:d:1224031
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    References listed on IDEAS

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    1. Mohamed L. Seghier, 2023. "ChatGPT: not all languages are equal," Nature, Nature, vol. 615(7951), pages 216-216, March.
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    Cited by:

    1. Humaid Al Naqbi & Zied Bahroun & Vian Ahmed, 2024. "Enhancing Work Productivity through Generative Artificial Intelligence: A Comprehensive Literature Review," Sustainability, MDPI, vol. 16(3), pages 1-37, January.

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