Deep-learning-based breast cancer stage prediction from H&E-stained whole-slide images in resource-constrained settings.

Bedőházi Z, Biricz A, Kilim O, Foster N, Gregus B, Tőkés AM, Pollner P, Csabai I, Knudsen BS

Open source

DOI: 10.1016/j.jpi.2026.100644
Published: 2026 Apr
Container: Journal of pathology informatics
Publisher: Not recorded
Open access: yes

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Cite this work

BibTeX

@article{allodium:10.1016/j.jpi.2026.100644,
  title = {Deep-learning-based breast cancer stage prediction from H\&E-stained whole-slide images in resource-constrained settings.},
  author = {Bedőházi Z and Biricz A and Kilim O and Foster N and Gregus B and Tőkés AM and Pollner P and Csabai I and Knudsen BS},
  year = {2026},
  journal = {Journal of pathology informatics},
  doi = {10.1016/j.jpi.2026.100644},
  url = {https://doi.org/10.1016/j.jpi.2026.100644}
}

RIS

TY  - JOUR
TI  - Deep-learning-based breast cancer stage prediction from H&E-stained whole-slide images in resource-constrained settings.
AU  - Bedőházi Z
AU  - Biricz A
AU  - Kilim O
AU  - Foster N
AU  - Gregus B
AU  - Tőkés AM
AU  - Pollner P
AU  - Csabai I
AU  - Knudsen BS
PY  - 2026
JO  - Journal of pathology informatics
DO  - 10.1016/j.jpi.2026.100644
UR  - https://doi.org/10.1016/j.jpi.2026.100644
ER  -

APA

Z, B., A, B., O, K., N, F., B, G., AM, T., P, P., I, C., & BS, K. (2026). Deep-learning-based breast cancer stage prediction from H&E-stained whole-slide images in resource-constrained settings.. Journal of pathology informatics. https://doi.org/10.1016/j.jpi.2026.100644

Source records

pubmed · retrieved 2026-09-26T00:32:29.412Z
europe-pmc · retrieved 2026-09-26T00:32:29.426Z
doaj · retrieved 2026-09-26T00:32:29.441Z