A new method for assessing chronic insomnia: Machine learning-based fusion of TCM observation digital features
This study emphasized convenient and non-invasive diagnostic methods for investigating specific facial and tongue features associated with chronic insomnia. A classification model for chronic insomnia has been developed through the integration of multiple features, enabling a more accurate assessment of insomnia severity and facilitating advancements in therapeutic interventions.
Authors
- Yu Wang (ORCID: https://orcid.org/0000-0002-8101-6228)
- Jiatuo Xu (ORCID: https://orcid.org/0000-0002-3498-2132)
- Xudong Huang (ORCID: https://orcid.org/0000-0002-4811-1901)
- Yulin Shi (ORCID: https://orcid.org/0000-0003-4379-8561)
- Jie Chen (ORCID: https://orcid.org/0000-0002-2658-9525)
- Xuemin Wang (ORCID: https://orcid.org/0000-0001-8897-5344)
- Zhentao Li (ORCID: https://orcid.org/0000-0001-9744-9944)
- Liang Xu (ORCID: https://orcid.org/0000-0002-6441-4443)
- Q. M. Chen (ORCID: https://orcid.org/0009-0002-8920-1716)
Institutions
- Tianjin University (CN)
- Shanghai Jiao Tong University (CN)
- Shanghai University of Traditional Chinese Medicine (CN)
- Shanghai Traditional Chinese Medicine Hospital (CN)
- Community Health Center (US)
- Wuhu Institute of Technology (CN)
- Shanghai Huangpu District Central Hospital (CN)
Publication Details
- Journal
- Digital Health
- Published
- 2025-05-01
- DOI
- https://doi.org/10.1177/20552076251393331
- Primary Topic
- Sleep and related disorders
- Type
- article
- Field-Weighted Citation Impact
- 0.00