Novel machine‐learning prediction tools for overall survival of patients with chondrosarcoma: Based on recursive partitioning analysis
This study successfully employed RPA to develop a user-friendly tool for personalized survival predictions in CHS. The decision tree models demonstrated robust predictive capabilities, with the interactive application facilitating clinical decision-making. Future prospective studies are recommended to validate these findings and further refine the predictive model.
Authors
- Qiyang Wang (ORCID: https://orcid.org/0000-0002-3054-4207)
- Sheng Lu (ORCID: https://orcid.org/0009-0001-7461-1416)
- Shanshan Yang (ORCID: https://orcid.org/0000-0003-4168-3496)
- Zhi Peng (ORCID: https://orcid.org/0000-0002-5261-6742)
- Xiong‐gang Yang
- Yīmíng Bào (ORCID: https://orcid.org/0000-0002-9922-9723)
Institutions
- Kunming University of Science and Technology (CN)
- Zunyi Medical University (CN)
- First People's Hospital of Yunnan Province (CN)
Publication Details
- Journal
- Cancer Medicine
- Published
- 2024-08-01
- DOI
- https://doi.org/10.1002/cam4.70058
- Citations
- 2
- Primary Topic
- Bone Tumor Diagnosis and Treatments
- Type
- article
- Field-Weighted Citation Impact
- 0.94