Reproducible and Interpretable Machine Learning-Based Radiomic Analysis for Overall Survival Prediction in Glioblastoma Multiforme
We identified and validated a clinical-radiomic model for stratification of patients into low and high-risk groups based on OS in patients with GBM using a multicenter retrospective dataset. Future work will focus on the use of deep learning-based features, with recently standardized convolutional filters on OS tasks.
Authors
- Xianfang Sun (ORCID: https://orcid.org/0000-0002-6114-0766)
- Emiliano Spezi (ORCID: https://orcid.org/0000-0002-1452-8813)
- S Thomas (ORCID: https://orcid.org/0000-0003-2766-9524)
- Abdulkerim Duman (ORCID: https://orcid.org/0000-0003-2747-1294)
- J.R. Powell
Institutions
- Maidstone and Tunbridge Wells NHS Trust (GB)
- Velindre NHS Trust (GB)
- Cardiff University (GB)
Publication Details
- Journal
- Cancers
- Published
- 2024-09-30
- DOI
- https://doi.org/10.3390/cancers16193351
- Citations
- 11
- Primary Topic
- Radiomics and Machine Learning in Medical Imaging
- Type
- article
- Field-Weighted Citation Impact
- 4.45
Funders
- Cardiff University
- Milli Eğitim Bakanliği