Skip to main content

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


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.

This is a preview of subscription content, access via your institution.


  1. 1.

    Chan LK, Wiseman J. Use of the one-minute preceptor as a teaching tool in the gross anatomy laboratory. Anat Sci Educ. 2011;4:235–8.

    Article  Google Scholar 

  2. 2.

    Devlin J, Chang MW, Lee K, Toutanova K. Bert: Pre-training of deep bidirectional transformers for language understanding. arXiv preprint. 2019, 1810.04805

  3. 3.

    Dong L, Yang N, Wang W, Wei F, Liu X, Wang Y, Gao J, Zhou M, Hon HW. Unified language model pre-training for natural language understanding and generation. Adv Neural Inf Process Syst. 2019, pp. 13063–13075.

  4. 4.

    Smith C, Finn G, Stewart J, McHanwel S. Anatomical society core regional anatomy syllabus for undergraduate medicine: The delphi process. J Anat. 2015;228.

  5. 5.

    Zhang Y, Li D, Wang Y, Fang Y, Xiao W. Abstract text summarization with a convolutional seq2seq model. Appl Sci. 2019;9(8):1665.

    Article  Google Scholar 

Download references


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

Author information



Corresponding author

Correspondence to Christopher See.

Ethics declarations

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.

Additional information

Publisher's Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Rights and permissions

Reprints and Permissions

About this article

Verify currency and authenticity via CrossMark

Cite this article

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. (2021).

Download citation


  • Anatomy education
  • Artificial intelligence
  • Machine learning
  • Chatbot
  • Natural language processing
  • Pedagogical innovation