Artifacts from the study "Explainable histomorphology-based survival prediction of glioblastoma, IDH-wildtype"
Abstract
This record includes artifacts supplementing the study "Explainable histomorphology-based survival prediction of glioblastoma, IDH-wildtype" (https://doi.org/10.48550/arXiv.2601.11691). Content: example_tiles.pdf: Example tiles decsribed in the study. sparse_autoencoder_checkpoint.pt: Checkpoint of the sparse autoencoder trained for the study. sparse_autoencoder.py: Python script implementing the sparse autoencoder PyTorch class, along with instructions on how to use it. The source code from the study is available at https://github.com/FraunhoferMEVIS/canconnect-study.
Fields of Study & Subjects
Radiomics and Machine Learning in Medical Imaging
Glioma Diagnosis and Treatment
AI in cancer detection
Publication details
- Journal / source
- arXiv (Cornell University)
- Publication date
- 28 January 2026
- Language
- EN
- Document type
- Preprint