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Using a Machine Learning Architecture to Create an AI-Powered Chatbot for Anatomy Education

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Abstract

Artificial Intelligence chatbots allow interactive dialogue-driven teaching of medical sciences. Open-source tools allow educators to adapt existing technology to create intelligent learning systems. We utilised an open-source machine learning architecture and fine-tuned it with a customised database to train an AI dialogue system to teach medical students anatomy.

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Funding

This study is kindly supported by a Teaching Development and Language Enhancement Grant from The Chinese University of Hong Kong.

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Authors and Affiliations

  1. LKS Faculty of Medicine, University of Hong Kong, Pokfulam, Hong Kong

    Yik Sum Li & Cynthia Sin Nga Lam

  2. School of Biomedical Sciences, Faculty of Medicine, The Chinese University of Hong Kong, Shatin, N.T, Hong Kong

    Christopher See

Authors
  1. Yik Sum Li
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  2. Cynthia Sin Nga Lam
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  3. Christopher See
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Corresponding author

Correspondence to Christopher See.

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Ethics Approval

This study has been approved by the Institutional Review Board of The Chinese University of Hong Kong (SBRE-20–043).

Informed Consent

Participation was undertaken on a voluntary basis by students who signed a written consent form as their agreement to participate.

Conflict of Interest

The authors declare no competing interests.

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Li, Y.S., Lam, C.S.N. & See, C. Using a Machine Learning Architecture to Create an AI-Powered Chatbot for Anatomy Education. Med.Sci.Educ. 31, 1729–1730 (2021). https://doi.org/10.1007/s40670-021-01405-9

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  • DOI: https://doi.org/10.1007/s40670-021-01405-9

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