Machine learning based predictive model and genetic mutation landscape for high-grade colorectal neuroendocrine carcinoma: a SEER database analysis with external validation
In this study, a refined machine learning predictive model was developed to assess the prognosis of HCNEC accurately and we briefly analyzed its genomic features, which might offer a valuable tool to address existing clinical challenges.
Authors
- Yi He (ORCID: https://orcid.org/0009-0005-6864-0404)
- Aishun Jin
- Rui‐Xin Wu (ORCID: https://orcid.org/0000-0003-0857-4239)
- Ya Li (ORCID: https://orcid.org/0000-0003-3881-2031)
- Song Mu
- Sihao Chen (ORCID: https://orcid.org/0000-0001-8416-4261)
Institutions
- Guiyang Medical University (CN)
- Affiliated Hospital of Guizhou Medical University (CN)
- The Affiliated Yongchuan Hospital of Chongqing Medical University (CN)
- Chongqing Medical University (CN)
Publication Details
- Journal
- Frontiers in Oncology
- Published
- 2025-01-29
- DOI
- https://doi.org/10.3389/fonc.2025.1509170
- Citations
- 2
- Primary Topic
- Neuroendocrine Tumor Research Advances
- Type
- article
- Field-Weighted Citation Impact
- 2.71
Funders
- Chongqing Postdoctoral Science Foundation
- Chongqing Medical University
- Centre Scientifique et Technique du Bâtiment