Integration of histopathological image features and multi-dimensional omics data in predicting molecular features and survival in glioblastoma
Our study indicated a certain prognostic value of HIF, and the integrated multi-omics model may enhance the prognostic prediction of GBM, offering improved accuracy and robustness for clinical application.
Authors
- Linyan Chen (ORCID: https://orcid.org/0000-0002-0888-247X)
- Yu Liu (ORCID: https://orcid.org/0000-0002-3858-7578)
- Zhengyong Li (ORCID: https://orcid.org/0000-0002-4374-9172)
- Yeqian Huang (ORCID: https://orcid.org/0000-0001-5416-1246)
- Yang Liu (ORCID: https://orcid.org/0000-0001-5752-5180)
- Zhenyu Zhang (ORCID: https://orcid.org/0000-0001-8985-7083)
- Zhiyuan Zhang (ORCID: https://orcid.org/0000-0002-5907-312X)
- Leizhen Huang (ORCID: https://orcid.org/0000-0002-8945-8231)
- Liu R (ORCID: https://orcid.org/0000-0001-9963-7092)
- Fengqin Song
Institutions
- Sichuan University (CN)
- West China Hospital of Sichuan University (CN)
- State Key Laboratory of Biotherapy
Publication Details
- Journal
- Frontiers in Medicine
- Published
- 2025-04-23
- DOI
- https://doi.org/10.3389/fmed.2025.1510793
- Citations
- 5
- Primary Topic
- Radiomics and Machine Learning in Medical Imaging
- Type
- article
- Field-Weighted Citation Impact
- 6.80