A machine learning-based model for predicting survival in patients with Rectosigmoid Cancer
We developed a prediction model based on the optimal machine learning, XGBoost, which can assist clinical decision-making and potentially extend the survival of patients with rectosigmoid junction cancer.
Authors
- Bingbing Chen (ORCID: https://orcid.org/0000-0001-5500-4998)
- Yifei Wang (ORCID: https://orcid.org/0000-0002-2371-4036)
- Jinhai Yu (ORCID: https://orcid.org/0000-0001-5865-606X)
Institutions
- Jilin University (CN)
- First Hospital of Jilin University (CN)
Publication Details
- Journal
- PLoS ONE
- Published
- 2025-03-25
- DOI
- https://doi.org/10.1371/journal.pone.0319248
- Primary Topic
- Colorectal Cancer Surgical Treatments
- Type
- article
- Field-Weighted Citation Impact
- 0.00