Predicting distant metastasis of bladder cancer using multiple machine learning models: a study based on the SEER database with external validation
The prediction model developed using three ML algorithms demonstrated strong accuracy and discriminative capability in predicting distant metastasis in patients with bladder cancer. This might help clinicians in understanding patient prognosis and in formulating personalized treatment strategies, ultimately improving the overall prognosis of patients with bladder cancer.
Authors
- Tao Zeng (ORCID: https://orcid.org/0000-0002-1145-2059)
- Jie Zhou (ORCID: https://orcid.org/0000-0002-1436-0969)
- Hai Chao Chao
- Xu-Guang Rao
- Jian Huang (ORCID: https://orcid.org/0000-0002-5992-2777)
- Xin Chang Zou
Institutions
- Nanchang University (CN)
- Second Affiliated Hospital of Nanchang University (CN)
Publication Details
- Journal
- Frontiers in Oncology
- Published
- 2024-12-13
- DOI
- https://doi.org/10.3389/fonc.2024.1477166
- Citations
- 2
- Primary Topic
- Bladder and Urothelial Cancer Treatments
- Type
- article
- Field-Weighted Citation Impact
- 1.15
Funders
- Innovative Research Group Project of the National Natural Science Foundation of China
- National Natural Science Foundation of China
- Jiangxi Provincial Department of Science and Technology