Current concerns and future directions of large language model ChatGPT in medicine: a machine-learning-driven global-scale bibliometric analysis
This study revealed ChatGPT's global attention and development patterns in different medical disciplines and geographical regions, its current global concerns, and future directions. This information will provide a critical reference for subsequent research and policymaking on LLMs throughout the entire field of medicine.
Authors
- Song‐Bin Guo (ORCID: https://orcid.org/0000-0001-5768-0922)
- Xiuyu Cai (ORCID: https://orcid.org/0000-0002-5251-9272)
- Zhen-Zhong Zhou
- Mei Li (ORCID: https://orcid.org/0000-0002-6769-4663)
- Dengyao Liu (ORCID: https://orcid.org/0000-0002-0735-0367)
- Yuan Meng (ORCID: https://orcid.org/0000-0001-9435-0260)
- Jing Li (ORCID: https://orcid.org/0000-0002-2037-5817)
- Hailong Li (ORCID: https://orcid.org/0000-0003-0652-6655)
- Wei-Juan Huang
- Xiaojie Fang (ORCID: https://orcid.org/0000-0002-1511-1841)
- L Q Luo (ORCID: https://orcid.org/0000-0002-6525-7240)
- Xiao-Peng Tian
Institutions
- Xinjiang Medical University (CN)
- Sun Yat-sen University (CN)
- Jinan University (CN)
- The Seventh Affiliated Hospital of Sun Yat-sen University (CN)
- Tumor Hospital of Xinjiang Medical University (CN)
- Guangdong Academy of Medical Sciences (CN)
- Sun Yat-sen University Cancer Center (CN)
Publication Details
- Journal
- International Journal of Surgery
- Published
- 2025-10-22
- DOI
- https://doi.org/10.1097/js9.0000000000003668
- Citations
- 10
- Primary Topic
- Artificial Intelligence in Healthcare and Education
- Type
- article
- Field-Weighted Citation Impact
- 6.54