The Relationship Between Computerized Face and Tongue Image Segmentation and Metabolic Parameters in Patients with Type 2 Diabetes Based on Machine Learning
This study demonstrated that metabolic status, renal and hepatic, cardiac, and thyroid function, the proportion of blood cells, and Hb in T2DM were intimately associated with facial and tongue features. The precise analysis of facial and tongue features through AI and advanced machine learning could be used to predict T2DM's conditions and progression.
Authors
- Ligang Zhou (ORCID: https://orcid.org/0000-0002-8512-6125)
- Song Wen (ORCID: https://orcid.org/0000-0001-6173-0507)
- Meiyuan Dong (ORCID: https://orcid.org/0000-0002-2897-9316)
- Yue Yuan (ORCID: https://orcid.org/0000-0001-8859-332X)
- Fufeng Li (ORCID: https://orcid.org/0000-0002-0566-3589)
- Jianlan Jin
- Lijiao Chen (ORCID: https://orcid.org/0000-0002-1892-4119)
- Yanyan Li (ORCID: https://orcid.org/0009-0003-1355-9065)
- Congcong Wang (ORCID: https://orcid.org/0000-0002-5661-8796)
- Yishu Ren
- Yifan Zhou (ORCID: https://orcid.org/0000-0002-1477-5777)
- Xinlu Yuan
- Zhimin Xu (ORCID: https://orcid.org/0000-0002-2567-3207)
- Min Gong (ORCID: https://orcid.org/0000-0003-3812-9611)
- Chenglin Xu (ORCID: https://orcid.org/0000-0002-1584-6282)
Institutions
- Fudan University (CN)
- Shanghai University of Traditional Chinese Medicine (CN)
- Pudong Medical Center (CN)
- Tianjin Medical University (CN)
Publication Details
- Journal
- Diabetes Metabolic Syndrome and Obesity
- Published
- 2024-10-01
- DOI
- https://doi.org/10.2147/dmso.s491897
- Citations
- 4
- Primary Topic
- Traditional Chinese Medicine Studies
- Type
- article
- Field-Weighted Citation Impact
- 2.86
Funders
- Natural Science Foundation of Shanghai
- Wenzhou Medical University
- National Natural Science Foundation of China
- Fudan University