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ChatGPT and Clinical Decision Support: Scope, Application, and Limitations

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Abstract

This study examines ChatGPT’s role in clinical decision support, by analyzing its scope, application, and limitations. By analyzing patient data and providing evidence-based recommendations, ChatGPT, an AI language model, can help healthcare professionals make well-informed decisions. This study examines ChatGPT’s use in clinical decision support, including diagnosis and treatment planning. However, it acknowledges limitations like biases, lack of contextual understanding, and human oversight and also proposes a framework for the future clinical decision support system. Understanding these factors will allow healthcare professionals to utilize ChatGPT effectively and make accurate clinical decisions. Further research is needed to understand the implications of using ChatGPT in healthcare settings and to develop safeguards for responsible use.

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Acknowledgements

The authors acknowledge that this article was partially generated by ChatGPT (powered by OpenAI’s language model, GPT; http://openai.com). The editing was performed by the authors.

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Author notes

  1. Jannatul Ferdush, Mahbuba Begum and Sakib Tanvir Hossain have contributed equally to this work.

Authors and Affiliations

  1. Department of Computer Science and Engineering, Jashore University of Science and Technology, Jashore, 7408, Bangladesh

    Jannatul Ferdush

  2. Department of Computer Science and Engineering, Mawlana Bhasani Science and Technology, Tangail, 1902, Bangladesh

    Mahbuba Begum

  3. Department of Mechanical Engineering, Khulna University of Engineering and Technology, Khulna, 9203, Bangladesh

    Sakib Tanvir Hossain

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  1. Jannatul Ferdush
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  2. Mahbuba Begum
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  3. Sakib Tanvir Hossain
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Correspondence to Jannatul Ferdush.

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The authors declare no conflict of interest

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Associate Editor Stefan M. Duma oversaw the review of this article.

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Ferdush, J., Begum, M. & Hossain, S.T. ChatGPT and Clinical Decision Support: Scope, Application, and Limitations. Ann Biomed Eng 52, 1119–1124 (2024). https://doi.org/10.1007/s10439-023-03329-4

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  • DOI: https://doi.org/10.1007/s10439-023-03329-4

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