privateST: a feasible framework for privacy-preserving spatial transcriptomics prediction from histopathology images.

Kim H, Kim M, Han B

DOI: 10.1038/s41598-026-55961-4
Published: 2026 Jun 3
Container: Scientific reports
Publisher: Not recorded
Open access: yes

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Cite this work

BibTeX

@article{allodium:10.1038/s41598-026-55961-4,
  title = {privateST: a feasible framework for privacy-preserving spatial transcriptomics prediction from histopathology images.},
  author = {Kim H and Kim M and Han B},
  year = {2026},
  journal = {Scientific reports},
  doi = {10.1038/s41598-026-55961-4},
  url = {https://doi.org/10.1038/s41598-026-55961-4}
}

RIS

TY  - JOUR
TI  - privateST: a feasible framework for privacy-preserving spatial transcriptomics prediction from histopathology images.
AU  - Kim H
AU  - Kim M
AU  - Han B
PY  - 2026
JO  - Scientific reports
DO  - 10.1038/s41598-026-55961-4
UR  - https://doi.org/10.1038/s41598-026-55961-4
ER  -

APA

H, K., M, K., & B, H. (2026). privateST: a feasible framework for privacy-preserving spatial transcriptomics prediction from histopathology images.. Scientific reports. https://doi.org/10.1038/s41598-026-55961-4

Source records

pubmed · retrieved 2026-09-26T18:22:50.476Z