AcuKG: a comprehensive knowledge graph for medical acupuncture
AcuKG is an open dataset that provides a structured and computational framework for acupuncture applications, bridging traditional practices with acupuncture research and cutting-edge LLM technologies.
Authors
- Yiming Li (ORCID: https://orcid.org/0009-0009-8784-1745)
- Li Zhou (ORCID: https://orcid.org/0000-0003-3874-4833)
- Cui Tao
- Yongqun He (ORCID: https://orcid.org/0000-0001-9189-9661)
- Qin Zhang (ORCID: https://orcid.org/0009-0009-5923-1384)
- Donghong Pei
- Xueqing Peng (ORCID: https://orcid.org/0000-0002-3296-3472)
- Na Hong (ORCID: https://orcid.org/0000-0001-6798-1761)
- Hua Xu (ORCID: https://orcid.org/0000-0002-5274-4672)
- Suyuan Peng (ORCID: https://orcid.org/0000-0002-8221-7574)
- Fang Li (ORCID: https://orcid.org/0000-0001-8865-7717)
- Yan Hu (ORCID: https://orcid.org/0009-0008-2413-5918)
- Yiwei Lu (ORCID: https://orcid.org/0000-0001-9549-3239)
- Jianfu Li (ORCID: https://orcid.org/0000-0002-9949-7007)
Institutions
- Brigham and Women's Hospital (US)
- The University of Texas MD Anderson Cancer Center (US)
- Harvard University (US)
- Chinese Academy of Medical Sciences & Peking Union Medical College (CN)
- University of Michigan (US)
- Yale University (US)
- Michigan Center for Translational Pathology (US)
- China Academy of Chinese Medical Sciences (CN)
- Mayo Clinic in Florida (US)
- National Science Library (CN)
- The University of Texas Health Science Center at Houston (US)
Publication Details
- Journal
- Journal of the American Medical Informatics Association
- Published
- 2025-09-27
- DOI
- https://doi.org/10.1093/jamia/ocaf179
- Citations
- 3
- Primary Topic
- Acupuncture Treatment Research Studies
- Type
- article
- Field-Weighted Citation Impact
- 7.14