Proposal and Assessment of a De-Identification Strategy to Enhance Anonymity of the Observational Medical Outcomes Partnership Common Data Model (OMOP-CDM) in a Public Cloud-Computing Environment: Anonymization of Medical Data Using Privacy Models. Jeon, S., Seo, J., Kim, S., Lee, J., Kim, J. H., Sohn, J. W., Moon, J., & Joo, H. J. J Med Internet Res, 22(11):e19597, 2020.
Proposal and Assessment of a De-Identification Strategy to Enhance Anonymity of the Observational Medical Outcomes Partnership Common Data Model (OMOP-CDM) in a Public Cloud-Computing Environment: Anonymization of Medical Data Using Privacy Models [link]Paper  doi  bibtex   
@article{RN22,
   author = {Jeon, S. and Seo, J. and Kim, S. and Lee, J. and Kim, J. H. and Sohn, J. W. and Moon, J. and Joo, H. J.},
   title = {Proposal and Assessment of a De-Identification Strategy to Enhance Anonymity of the Observational Medical Outcomes Partnership Common Data Model (OMOP-CDM) in a Public Cloud-Computing Environment: Anonymization of Medical Data Using Privacy Models},
   journal = {J Med Internet Res},
   volume = {22},
   number = {11},
   pages = {e19597},
   ISSN = {1438-8871 (Electronic)
1438-8871 (Linking)},
   DOI = {v22i11e19597 [pii]
10.2196/19597},
   url = {https://www.ncbi.nlm.nih.gov/pubmed/33177037},
   year = {2020},
   type = {Journal Article}
}

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