DeepSeek empowers medical education: characteristics, impacts and responses

Corresponding author: Fanqi WU, 2278533302@qq.com

DOI: 10.12201/bmr.202504.00033

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  Abstract: Abstract: Purpose/Significance At present,the rapid development of domestic artificial intelligence (AI) large language model (LLM) DeepSeek has affected many fields such as communications,finance,medical treatment,and automobiles. As medical educators,we should be keenly aware of the opportunities and challenges that DeepSeek brings to medical education. Method/Process This paper focuses on the three characteristics of DeepSeek's:technical architecture,open source strategy,localization advantage,and visual reasoning,exploring how DeepSeek can better empower talent cultivation through the impact of teaching resources,teaching experience,and teaching ecology compared with LLMs represented by GPT. Result/Conclusion Medical educators should rethink the nature of education and learning to ensure that DeepSeek is truly and effectively applied to medical education.

  Key words: artificial intelligence; large language model; DeepSeek; medical education; education and teaching

  Submit time: 26 May 2025

  Copyright: The copyright holder for this preprint is the author/funder, who has granted biomedRxiv a license to display the preprint in perpetuity.
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