A Machine Learning Framework for Prognostic Modeling in Stage III Colon Cancer
This study identifies key prognostic factors influencing survival in stage III colon cancer and demonstrates that machine learning-based approaches can complement conventional statistical methods. The integration of clinical and treatment-related variables may improve individualized risk stratification and support clinical decision-making. These findings may also guide future large-scale, multicenter, and prospective studies.
Authors
- Öznur Bal (ORCID: https://orcid.org/0000-0002-6901-2646)
- Doğan Uncu (ORCID: https://orcid.org/0000-0002-0929-3271)
- Efnan Algın (ORCID: https://orcid.org/0000-0002-8917-9267)
- Sevil Uygun İlikhan (ORCID: https://orcid.org/0000-0002-0162-5729)
- Seli̇n Aktürk Esen (ORCID: https://orcid.org/0000-0002-3426-9505)
- Hilal Arslan (ORCID: https://orcid.org/0000-0002-6449-6952)
- Şebnem Yaman
- Rümeysa Sungur
- Hatice Rüveyda Akça (ORCID: https://orcid.org/0009-0005-3745-5222)
Institutions
- Ankara University (TR)
- Bilkent University (TR)
- Memorial Ankara Hospital (TR)
- Ankara Bilkent City Hospital (TR)
Publication Details
- Journal
- Journal of Clinical Medicine
- Published
- 2026-04-17
- DOI
- https://doi.org/10.3390/jcm15083091
- Primary Topic
- Colorectal Cancer Surgical Treatments
- Type
- article
- Field-Weighted Citation Impact
- 0.00