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Large language models for medicine: a survey

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Abstract

To address challenges in the digital economy’s landscape of digital intelligence, large language models (LLMs) have been developed. Improvements in computational power and available resources have significantly advanced LLMs, allowing their integration into diverse domains for human life. Medical LLMs are essential application tools with potential across various medical scenarios. In this paper, we review LLM developments, focusing on the requirements and applications of medical LLMs. We provide a concise overview of existing models, aiming to explore advanced research directions and benefit researchers for future medical applications. We emphasize the advantages of medical LLMs in applications, as well as the challenges encountered during their development. Finally, we suggest directions for technical integration to mitigate challenges and potential research directions for the future of medical LLMs, aiming to meet the demands of the medical field better.

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Acknowledgements

This research was supported in part by the National Natural Science Foundation of China (No. 62272196), the Natural Science Foundation of Guangdong Province (No. 2022A1515011861), Guangzhou Basic and Applied Basic Research Foundation (No. 2024A04J9971).

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Authors and Affiliations

  1. College of Cyber Security, Jinan University, Guangzhou, 510632, China

    Yanxin Zheng, Wensheng Gan & Zefeng Chen

  2. School of Information Engineering, Guangdong Eco-Engineering Polytechnic, Guangzhou, 510520, China

    Zhenlian Qi

  3. Shenzhen People’s Hospital (The Second Clinical Medical College, Jinan University), Shenzhen, 518020, China

    Qian Liang

  4. Department of Computer Science, University of Illinois Chicago, Chicago, IL, 60607, USA

    Philip S. Yu

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  1. Yanxin Zheng
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  2. Wensheng Gan
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  3. Zefeng Chen
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  4. Zhenlian Qi
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  5. Qian Liang
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Contributions

Yanxin Zheng: paper reading and review, writing original draft. Wensheng Gan: conceptualization, review and editing, supervisor. Zefeng Chen and Zhenlian Qi: conceptualization, review and editing. Qian Liang and Philip S. Yu: review and editing.

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Correspondence to Yanxin Zheng or Wensheng Gan.

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Zheng, Y., Gan, W., Chen, Z. et al. Large language models for medicine: a survey. Int. J. Mach. Learn. & Cyber. (2024). https://doi.org/10.1007/s13042-024-02318-w

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