PHSP-Net: Personalized Habitat-Aware Deep Learning for Multi-Center Glioblastoma Survival Prediction Using Multiparametric MRI
PHSP-Net demonstrates high predictive accuracy, robust cross-center generalization and improved interpretability in multi-center GBM cohorts. By enabling personalized habitat visualization, it offers a promising non-invasive tool for prognostic assessment and individualized clinical decision making in GBM.
Authors
- Tianci Liu (ORCID: https://orcid.org/0000-0002-4601-9554)
- Dong Huang (ORCID: https://orcid.org/0000-0002-9746-0032)
- Yang Liu (ORCID: https://orcid.org/0000-0002-0984-5128)
- Chengwei Chen (ORCID: https://orcid.org/0000-0001-6293-5387)
- Yuefei Feng
- Jie Wei (ORCID: https://orcid.org/0000-0002-4206-1376)
- Yao Zheng (ORCID: https://orcid.org/0000-0002-1708-025X)
Institutions
- Air Force Engineering University (CN)
- Xijing Hospital (CN)
- Air Force Medical University (CN)
Publication Details
- Journal
- Bioengineering
- Published
- 2025-09-15
- DOI
- https://doi.org/10.3390/bioengineering12090978
- Primary Topic
- Radiomics and Machine Learning in Medical Imaging
- Type
- article
- Field-Weighted Citation Impact
- 0.00
Funders
- National Natural Science Foundation of China