Scalable and Privacy-Conscious End-to-End Processing of Large-Scale Clinical Data for Precision Medicine: Empirical Evaluation Study.

Lee J, Hwang S, Lee KH

Open source

DOI: 10.2196/83487
Published: 2026 Mar 4
Container: JMIR medical informatics
Publisher: Not recorded
Open access: yes

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Cite this work

BibTeX

@article{allodium:10.2196/83487,
  title = {Scalable and Privacy-Conscious End-to-End Processing of Large-Scale Clinical Data for Precision Medicine: Empirical Evaluation Study.},
  author = {Lee J and Hwang S and Lee KH},
  year = {2026},
  journal = {JMIR medical informatics},
  doi = {10.2196/83487},
  url = {https://doi.org/10.2196/83487}
}

RIS

TY  - JOUR
TI  - Scalable and Privacy-Conscious End-to-End Processing of Large-Scale Clinical Data for Precision Medicine: Empirical Evaluation Study.
AU  - Lee J
AU  - Hwang S
AU  - Lee KH
PY  - 2026
JO  - JMIR medical informatics
DO  - 10.2196/83487
UR  - https://doi.org/10.2196/83487
ER  -

APA

J, L., S, H., & KH, L. (2026). Scalable and Privacy-Conscious End-to-End Processing of Large-Scale Clinical Data for Precision Medicine: Empirical Evaluation Study.. JMIR medical informatics. https://doi.org/10.2196/83487

Source records

pubmed · retrieved 2026-11-10T06:48:19.588Z
europe-pmc · retrieved 2026-11-10T06:48:19.597Z
doaj · retrieved 2026-11-10T06:48:19.612Z