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The DOI matches its Crossref record; 113 of the 120 references it cites were found in a registry or an index, and 7 are not checked yet.

The application of large language models in medicine: A scoping review

Open access
Meng, Xiangbin, Yan, Xiangyu, Zhang, Kuo, Liu, Da, Cui, Xiaojuan, Yang, Yaodong, Zhang, Muhan, Cao, Chunxia, Wang, Jingjia, Wang, Xuliang, Gao, Jun, Wang, Yuan-Geng-Shuo, Ji, Jia-ming, Qiu, Zifeng, Li, Muzi, Qian, Cheng, Guo, Tianze, Ma, Shuangquan, Wang, Zeying, Guo, Zexuan, Lei, Youlan, Shao, Chunli, Wang, Wenyao, Fan, Haojun, Tang, Yi-Da·2024·iScience
DOI 10.1016/j.isci.2024.109713PMC PMC11091685
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Abstract

This study systematically reviewed the application of large language models (LLMs) in medicine, analyzing 550 selected studies from a vast literature search. LLMs like ChatGPT transformed healthcare by enhancing diagnostics, medical writing, education, and project management. They assisted in drafting medical documents, creating training simulations, and streamlining research processes. Despite their growing utility in assisted diagnosis and improving doctor-patient communication, challenges persisted, including limitations in contextual understanding and the risk of over-reliance. The surge in LLM-related research indicated a focus on medical writing, diagnostics, and patient communication, but highlighted the need for careful integration, considering validation, ethical concerns, and the balance with traditional medical practice. Future research directions suggested a focus on multimodal LLMs, deeper algorithmic understanding, and ensuring responsible, effective use in healthcare.

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Crossref · 10.1016/j.isci.2024.109713

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Graphical abstract CC BY-NC-ND · PubMed Central
Figure 1 Search results and study inclusion For a Figure360 author presentation of Figure 1, see https://doi.org/10.1016/j.isci.2024.109713.
Figure 1 Search results and study inclusion For a Figure360 author presentation of Figure 1, see https://doi.org/10.1016/j.isci.2024.109713.CC BY-NC-ND · PubMed Central
Figure 2 Monthly breakdown of LLMs medical research: original vs. non-original publications For a Figure360 author presentation of Figure 2, see https://doi.org/10.1016/j.isci.2024.109713.
Figure 2 Monthly breakdown of LLMs medical research: original vs. non-original publications For a Figure360 author presentation of Figure 2, see https://doi.org/10.1016/j.isci.2024.109713.CC BY-NC-ND · PubMed Central
Figure 3 Heatmap of LLMs applications in medical research by organ system For a Figure360 author presentation of Figure 3, see https://doi.org/10.1016/j.isci.2024.109713.
Figure 3 Heatmap of LLMs applications in medical research by organ system For a Figure360 author presentation of Figure 3, see https://doi.org/10.1016/j.isci.2024.109713.CC BY-NC-ND · PubMed Central
Figure 4 Global spread of LLMs medical research by country For a Figure360 author presentation of Figure 4, see https://doi.org/10.1016/j.isci.2024.109713.
Figure 4 Global spread of LLMs medical research by country For a Figure360 author presentation of Figure 4, see https://doi.org/10.1016/j.isci.2024.109713.CC BY-NC-ND · PubMed Central
Figure 5 Comparative visualization of LLMs medical contributions across nations For a Figure360 author presentation of Figure 5, see https://doi.org/10.1016/j.isci.2024.109713. (A) Distribution of disease organ publications in research by country. (B) Comparative overview of medical field publications by country.
Figure 5 Comparative visualization of LLMs medical contributions across nations For a Figure360 author presentation of Figure 5, see https://doi.org/10.1016/j.isci.2024.109713. (A) Distribution of disease organ publications in research by country. (B) Comparative overview of medical field publications by country.CC BY-NC-ND · PubMed Central

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Research works printed but not linked: 2

  1. Thirunavukarasu, 2023, Large language models in medicine, Nat. Med., 29, 1930, 10.1038/s41591-023-02448-8 · DOI · Paper page
  2. Chen, 2023, Large language models in biomedical natural language processing: benchmarks, baselines, and recommendations, arXiv

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Metadata

Authors
Meng, X., Yan, X., Zhang, K., Liu, D., Cui, X., Yang, Y., Zhang, M., Cao, C., Wang, J., Wang, X., Gao, J., Wang, Y.-G.-S., Ji, J.-M., Qiu, Z., Li, M., Qian, C., Guo, T., Ma, S., Wang, Z., Guo, Z., Lei, Y., Shao, C., Wang, W., Fan, H., & Tang, Y.-D.
Affiliations
  • Peking University (CN)
  • Tianjin University (CN)
  • Chinese Academy of Medical Sciences & Peking Union Medical College (CN)
  • Hebei Medical University (CN)
  • Peking University Third Hospital (CN)
  • Beihang University (CN)
Corresponding author
  • Fan, Haojun
  • Tang, Yi-Da
ORCID
Venue
iScience
Publisher
Elsevier BV
Published
2024-05
Volume
27
Issue
5
Pages
109713
ISSN
2589-0042 (ISSN-L)
DOI
10.1016/j.isci.2024.109713
PMC
PMC11091685
OpenAlex
W4395052272
Cited by
414
References
114
Citations by year
2026: 188 · 2025: 188 · 2024: 38
FWCI
9.44
Type
journal article
Language
en
Open access
Licence
Locations
  • iScience (publishedVersion, cc-by-nc-nd)
  • PubMed Central (publishedVersion, cc-by-nc-nd)
  • PubMed (publishedVersion)
  • DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion)
Funders
  • National Key Research and Development Program of China Stem Cell and Translational Research (2020YFC2004705)
  • National Natural Science Foundation of China (81825003, 82270376, 91957123)
  • China Scholarship Council (CSCF2021A04)
  • CAMS Innovation Fund for Medical Sciences
  • Chinese Academy of Meteorological Sciences (2021-I2M-5-003, T-B-119)
  • National Key Research and Development Program of China
  • Beijing Municipal Science and Technology Commission, Adminitrative Commission of Zhongguancun Science Park
  • Beijing Nova Program (Z201100006820002)
Topics
  • Health Sciences › Medicine › Health Informatics › Artificial Intelligence in Healthcare and Education
  • Health Sciences › Health Professions › Health Information Management › Artificial Intelligence in Healthcare
  • Physical Sciences › Computer Science › Artificial Intelligence › Machine Learning in Healthcare
Keywords
large language models, ChatGPT, medical applications of AI, medical diagnostics, medical writing, medical education, training simulation, physician-patient communication, overreliance on AI, multimodal large language models, ethics of AI in healthcare

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