Privacy-Preserving Framework for Multi-Institutional Medical Time-Series Analysis via Homomorphic Encryption: Design and Development Study.

Lu Y, Tian Y, Zhou T, Xia J, Zhao Z, Sun H, Liu K, Li J

Open source

DOI: 10.2196/87306
Published: 2026 Aug 7
Container: JMIR formative research
Publisher: Not recorded
Open access: yes

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Cite this work

BibTeX

@article{allodium:10.2196/87306,
  title = {Privacy-Preserving Framework for Multi-Institutional Medical Time-Series Analysis via Homomorphic Encryption: Design and Development Study.},
  author = {Lu Y and Tian Y and Zhou T and Xia J and Zhao Z and Sun H and Liu K and Li J},
  year = {2026},
  journal = {JMIR formative research},
  doi = {10.2196/87306},
  url = {https://doi.org/10.2196/87306}
}

RIS

TY  - JOUR
TI  - Privacy-Preserving Framework for Multi-Institutional Medical Time-Series Analysis via Homomorphic Encryption: Design and Development Study.
AU  - Lu Y
AU  - Tian Y
AU  - Zhou T
AU  - Xia J
AU  - Zhao Z
AU  - Sun H
AU  - Liu K
AU  - Li J
PY  - 2026
JO  - JMIR formative research
DO  - 10.2196/87306
UR  - https://doi.org/10.2196/87306
ER  -

APA

Y, L., Y, T., T, Z., J, X., Z, Z., H, S., K, L., & J, L. (2026). Privacy-Preserving Framework for Multi-Institutional Medical Time-Series Analysis via Homomorphic Encryption: Design and Development Study.. JMIR formative research. https://doi.org/10.2196/87306

Source records

pubmed · retrieved 2026-09-25T03:37:20.852Z
europe-pmc · retrieved 2026-09-25T03:37:20.889Z
doaj · retrieved 2026-09-25T03:37:20.852Z