Construction of a risk prediction model for postoperative deep vein thrombosis in colorectal cancer patients based on machine learning algorithms
The machine learning algorithms effectively predicted postoperative lower limb deep vein thrombosis in colorectal cancer patients. The XGBoost model demonstrated strong potential for improving early detection and treatment in clinical settings.
Authors
- Xujian Shu (ORCID: https://orcid.org/0000-0001-5163-8555)
- Xinjun Liu (ORCID: https://orcid.org/0000-0001-9003-9299)
- Yifan Jiang (ORCID: https://orcid.org/0000-0002-4084-9194)
- Yejiang Zhou
Institutions
- Southwest Medical University (CN)
- Affiliated Hospital of Southwest Medical University (CN)
Publication Details
- Journal
- Frontiers in Oncology
- Published
- 2024-11-27
- DOI
- https://doi.org/10.3389/fonc.2024.1499794
- Citations
- 8
- Primary Topic
- Venous Thromboembolism Diagnosis and Management
- Type
- article
- Field-Weighted Citation Impact
- 4.39