Machine learning and the nomogram as the accurate tools for predicting postoperative malnutrition risk in esophageal cancer patients
Both machine learning and the nomogram provide accurate tools for predicting postoperative malnutrition risk in esophageal cancer patients. While RF showed marginally higher predictive performance, the nomogram offers superior clinical interpretability, making it a practical option for individualized risk stratification.
Authors
- X. Chen
- Jianfang Ke
- Mingfang Yan (ORCID: https://orcid.org/0000-0001-5018-7860)
- Zhenmeng Lin (ORCID: https://orcid.org/0000-0003-4514-8626)
- H Isaac Chen (ORCID: https://orcid.org/0000-0001-5188-2283)
- Hao He (ORCID: https://orcid.org/0000-0001-7070-3260)
Institutions
- Fujian Medical University (CN)
- First Affiliated Hospital of Fujian Medical University (CN)
- Fujian Provincial Cancer Hospital (CN)
Publication Details
- Journal
- Frontiers in Nutrition
- Published
- 2025-06-18
- DOI
- https://doi.org/10.3389/fnut.2025.1606470
- Citations
- 4
- Primary Topic
- Nutrition and Health in Aging
- Type
- article
- Field-Weighted Citation Impact
- 4.66
Funders
- Natural Science Foundation of Fujian Province
- Fujian Medical University