This paper is in the following e-collection/theme issue:

Ethics, Privacy, and Legal Issues (458) Clinical Informatics (919) Secondary Use of Clinical Data for Research and Surveillance (326)

Published on in Vol 22, No 11 (2020): November

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/19597, first published .
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

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

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

Authors of this article:

Seungho Jeon1 Author Orcid Image ;   Jeongeun Seo1 Author Orcid Image ;   Sukyoung Kim1 Author Orcid Image ;   Jeongmoon Lee2 Author Orcid Image ;   Jong-Ho Kim3 Author Orcid Image ;   Jang Wook Sohn4 Author Orcid Image ;   Jongsub Moon1 Author Orcid Image ;   Hyung Joon Joo5 Author Orcid Image
Article Authors Cited by (6) Tweetations (3) Metrics

Altmetric

Altmetric discovers Social Media mentions. Click the ‘See more details’ link for a full report.

Dimensions

Dimensions discovers Citations. Click the ‘details’ link for a full report.

Metrics Since Publication

Download .csv
Daily | Monthly | Annually