Machine learning-based nomogram for distinguishing between supratentorial extraventricular ependymoma and supratentorial glioblastoma
The nomogram could serve as a valuable tool for non-invasively discriminating between STEE and GBM.
Authors
- Rui Li (ORCID: https://orcid.org/0000-0002-9425-0523)
- Weijiao Chen
- Min‐Hsien Wu (ORCID: https://orcid.org/0000-0002-3507-3512)
- Lizhao Huang
- Ling Chen (ORCID: https://orcid.org/0000-0002-9748-4376)
- Yao Li (ORCID: https://orcid.org/0000-0002-7195-5774)
- Tao Li (ORCID: https://orcid.org/0000-0003-3831-901X)
- Lifang Tang
- Chuyun Tang
Institutions
- Guangxi Medical University (CN)
- Liuzhou Maternal and Child Health Hospital (CN)
- Liuzhou General Hospital (CN)
- First Affiliated Hospital of GuangXi Medical University (CN)
- Fourth Affiliated Hospital of Guangxi Medical University (CN)
Publication Details
- Journal
- Frontiers in Oncology
- Published
- 2024-09-09
- DOI
- https://doi.org/10.3389/fonc.2024.1443913
- Citations
- 1
- Primary Topic
- Glioma Diagnosis and Treatment
- Type
- article
- Field-Weighted Citation Impact
- 0.44
Funders
- Guangxi Zhuang Region Health Department