Improving the detection of privacy risk in synthetic EHRs

Introduction: Nowadays, hospitals commonly store electronic health records (EHRs) but, due to privacy protection laws, this data can only be distributed under severe constraints. Recent research aims to solve this problem by fitting a generative model to a cohort in a secure environment and creating [for full text, please go to the a.m. URL]

Institutions

Universität Hamburg (DE)
University Medical Center Hamburg-Eppendorf (DE)

Publication Details

Journal: German Medical Science (German Research Foundation)
Published: 2025-11-03
DOI: https://doi.org/10.3205/25gmds135
Primary Topic: Privacy-Preserving Technologies in Data
Type: article
Field-Weighted Citation Impact: 0.00

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article

Improving the detection of privacy risk in synthetic EHRs

Nov 3, 2025

German Medical Science (German Research Foundation)

Privacy-Preserving Technologies in Data

article

Improving the detection of privacy risk in synthetic EHRs

November 3, 2025article en

Abstract

German Medical Science (German Research Foundation)

Universität Hamburg (DE), University Medical Center Hamburg-Eppendorf (DE)

Openalex Percentile: Top 23%

Privacy-Preserving Technologies in Data

DOI Open Access PDF OpenAlex

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Improving the detection of privacy risk in synthetic EHRs · German Medical Science (German Research Foundation) (2025) | TGRS Research Map | TGRS