A Machine Learning Approach to Differentiate Cold and Hot Syndrome in Viral Pneumonia Integrating Traditional Chinese Medicine and Modern Medicine: Machine Learning Model Development and Validation
This pioneering study integrates the theory of TCM cold and hot syndromes with modern laboratory-based tests through machine learning. The developed model offers a novel approach for differentiating cold and hot syndromes in viral pneumonia, enabling practitioners to identify the syndrome quickly and efficiently, thereby supporting more informed clinical decision-making. Additionally, this research provides new insights into the modernization and scientific interpretation of TCM syndrome differentiation.
Authors
- Yongqi Liu (ORCID: https://orcid.org/0000-0003-2090-0017)
- Xiaojie Jin (ORCID: https://orcid.org/0000-0002-1467-6269)
- J. Li (ORCID: https://orcid.org/0000-0001-6073-4055)
- Qian Gao (ORCID: https://orcid.org/0009-0008-5035-484X)
- Y Wang (ORCID: https://orcid.org/0000-0003-2223-0619)
- Zhiming Zhang (ORCID: https://orcid.org/0000-0001-8555-3859)
- Jiali Zhao
- Shuyan Li (ORCID: https://orcid.org/0000-0001-7028-4166)
- Yuhan Huang (ORCID: https://orcid.org/0009-0000-0995-3455)
- L. G. Shao (ORCID: https://orcid.org/0009-0009-2092-6461)
- Jiarui Wang (ORCID: https://orcid.org/0009-0005-9890-2698)
- Ling Li (ORCID: https://orcid.org/0000-0002-9349-8332)
Institutions
- Xuzhou Medical College (CN)
- Gansu University of Traditional Chinese Medicine (CN)
- Gansu Provincial Hospital (CN)
- Lanzhou University (CN)
Publication Details
- Journal
- JMIR Medical Informatics
- Published
- 2025-07-16
- DOI
- https://doi.org/10.2196/64725
- Citations
- 2
- Primary Topic
- Traditional Chinese Medicine Studies
- Type
- article
- Field-Weighted Citation Impact
- 4.76