Identification and optimization of relevant factors for chronic kidney disease in abdominal obesity patients by machine learning methods: insights from NHANES 2005–2018
CatBoost models, along with glycolipid metabolism indexes and dietary antioxidant intake, are effective for early CKD detection in patients with abdominal obesity.
Authors
- Xiangling Deng
- Huixia Zhou
- Ronghua Jin (ORCID: https://orcid.org/0000-0002-6035-2425)
- Hualin Cao (ORCID: https://orcid.org/0009-0004-0881-4073)
- Yuandong Tao
- Hengyu Gao
- Xiaoye Chen (ORCID: https://orcid.org/0000-0003-1636-7264)
- Mengyang He
- Kuan Lu
- Wenchao Li (ORCID: https://orcid.org/0000-0002-9388-9261)
- Pin Li (ORCID: https://orcid.org/0000-0003-4508-3762)
- Wenquan Zhou (ORCID: https://orcid.org/0009-0009-1924-1131)
- Lifei Ma
Institutions
- Chinese PLA General Hospital (CN)
- The People's Hospital of Guangxi Zhuang Autonomous Region (CN)
Publication Details
- Journal
- Lipids in Health and Disease
- Published
- 2024-11-26
- DOI
- https://doi.org/10.1186/s12944-024-02384-7
- Citations
- 5
- Primary Topic
- Nutritional Studies and Diet
- Type
- article
- Field-Weighted Citation Impact
- 2.71