Clustering of patient-derived laboratory data: A privacy-preserving distributed approach to enhance clinical laboratory quality control and regional external quality assessment
- DOI
- 10.1371/journal.pone.0359083
- Published
- 2026-10-16
- Container
- PLOS One
- Publisher
- Public Library of Science (PLoS)
- Open access
- unknown
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Cite this work
BibTeX
@article{allodium:10.1371/journal.pone.0359083,
title = {Clustering of patient-derived laboratory data: A privacy-preserving distributed approach to enhance clinical laboratory quality control and regional external quality assessment},
author = {Chao Song and Qian Chen and Chunsheng Qu and Liqing Xu and Zhiming Shan and Jun Zhou and Weixing Li},
year = {2026},
journal = {PLOS One},
doi = {10.1371/journal.pone.0359083},
url = {https://doi.org/10.1371/journal.pone.0359083}
}RIS
TY - JOUR TI - Clustering of patient-derived laboratory data: A privacy-preserving distributed approach to enhance clinical laboratory quality control and regional external quality assessment AU - Chao Song AU - Qian Chen AU - Chunsheng Qu AU - Liqing Xu AU - Zhiming Shan AU - Jun Zhou AU - Weixing Li PY - 2026 JO - PLOS One DO - 10.1371/journal.pone.0359083 UR - https://doi.org/10.1371/journal.pone.0359083 ER -
APA
Song, C., Chen, Q., Qu, C., Xu, L., Shan, Z., Zhou, J., & Li, W. (2026). Clustering of patient-derived laboratory data: A privacy-preserving distributed approach to enhance clinical laboratory quality control and regional external quality assessment. PLOS One. https://doi.org/10.1371/journal.pone.0359083
Source records
- crossref · retrieved 2026-11-10T08:53:57.344Z