Foundation artificial intelligence models enable high-accuracy diagnostic differentiation of hybrid neurofibroma/schwannoma using whole-slide images.
- DOI
- 10.1016/j.jpi.2026.100700
- Published
- 2026 Aug
- 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.2026.100700,
title = {Foundation artificial intelligence models enable high-accuracy diagnostic differentiation of hybrid neurofibroma/schwannoma using whole-slide images.},
author = {Hellmann F and Anokhin M and Schimmler P and Tippner D and Plontke S and Kresbach C and Mensah M and André E and Harder A},
year = {2026},
journal = {Journal of pathology informatics},
doi = {10.1016/j.jpi.2026.100700},
url = {https://doi.org/10.1016/j.jpi.2026.100700}
}RIS
TY - JOUR TI - Foundation artificial intelligence models enable high-accuracy diagnostic differentiation of hybrid neurofibroma/schwannoma using whole-slide images. AU - Hellmann F AU - Anokhin M AU - Schimmler P AU - Tippner D AU - Plontke S AU - Kresbach C AU - Mensah M AU - André E AU - Harder A PY - 2026 JO - Journal of pathology informatics DO - 10.1016/j.jpi.2026.100700 UR - https://doi.org/10.1016/j.jpi.2026.100700 ER -
APA
F, H., M, A., P, S., D, T., S, P., C, K., M, M., E, A., & A, H. (2026). Foundation artificial intelligence models enable high-accuracy diagnostic differentiation of hybrid neurofibroma/schwannoma using whole-slide images.. Journal of pathology informatics. https://doi.org/10.1016/j.jpi.2026.100700
Source records
- pubmed · retrieved 2026-09-26T01:40:19.103Z