Pediatric brain tumor classification using digital pathology and deep learning: Evaluation of SOTA methods on a multi-center Swedish cohort.
- DOI
- 10.1111/bpa.70029
- Published
- 2026 Jan
- Container
- Brain pathology (Zurich, Switzerland)
- Publisher
- Not recorded
- Open access
- yes
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Cite this work
BibTeX
@article{allodium:10.1111/bpa.70029,
title = {Pediatric brain tumor classification using digital pathology and deep learning: Evaluation of SOTA methods on a multi-center Swedish cohort.},
author = {Tampu IE and Nyman P and Spyretos C and Blystad I and Shamikh A and Prochazka G and de Ståhl TD and Sandgren J and Lundberg P and Haj-Hosseini N},
year = {2026},
journal = {Brain pathology (Zurich, Switzerland)},
doi = {10.1111/bpa.70029},
url = {https://doi.org/10.1111/bpa.70029}
}RIS
TY - JOUR TI - Pediatric brain tumor classification using digital pathology and deep learning: Evaluation of SOTA methods on a multi-center Swedish cohort. AU - Tampu IE AU - Nyman P AU - Spyretos C AU - Blystad I AU - Shamikh A AU - Prochazka G AU - de Ståhl TD AU - Sandgren J AU - Lundberg P AU - Haj-Hosseini N PY - 2026 JO - Brain pathology (Zurich, Switzerland) DO - 10.1111/bpa.70029 UR - https://doi.org/10.1111/bpa.70029 ER -
APA
IE, T., P, N., C, S., I, B., A, S., G, P., TD, D. S., J, S., P, L., & N, H. (2026). Pediatric brain tumor classification using digital pathology and deep learning: Evaluation of SOTA methods on a multi-center Swedish cohort.. Brain pathology (Zurich, Switzerland). https://doi.org/10.1111/bpa.70029
Source records
- pubmed · retrieved 2026-09-26T06:14:13.944Z
- europe-pmc · retrieved 2026-09-26T06:14:13.953Z