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The Costs of Anonymization: Case Study Using Clinical Data
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What this work says
Outgoing claims: the papers this work cites, builds on, or argues with.
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Nonrandomized Real‐World Evidence to Support Regulatory Decision Making: Process for a Randomized Trial Replication Project
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Flexible data anonymization using ARX—Current status and challenges ahead
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Elements of Statistical Disclosure Control
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Identifiability in biobanks: models, measures, and mitigation strategies
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The German National Pandemic Cohort Network (NAPKON): rationale, study design and baseline characteristics
inferredcites →https://doi.org/10.1016/j.cose.2015.05.002openalex-snapshot
A taxonomy for privacy enhancing technologies
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Challenges of data sharing in European Covid-19 projects: A learning opportunity for advancing pandemic preparedness and response
inferredcites →https://doi.org/10.1017/jme.2021.67openalex-snapshot
Transparency of Regulatory Data across the European Medicines Agency, Health Canada, and US Food and Drug Administration
inferredcites →https://doi.org/10.1038/s41591-022-02080-yopenalex-snapshot
Implementing clinical trial data sharing requires training a new generation of biomedical researchers
inferredcites →https://doi.org/10.1038/s41597-020-00773-yopenalex-snapshot
Design and evaluation of a data anonymization pipeline to promote Open Science on COVID-19
inferredcites →https://doi.org/10.1038/s41597-022-01561-6openalex-snapshot
Utility-driven assessment of anonymized data via clustering
inferredcites →https://doi.org/10.1038/sdata.2016.18openalex-snapshot
The FAIR Guiding Principles for scientific data management and stewardship
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Die COVID-19 Pandemie als Herausforderung und Chance für Register in der Versorgungsforschung: Erfahrungen aus Lean European Open Survey on SARS-CoV-2 Infected Patients (LEOSS)
inferredcites →https://doi.org/10.1073/pnas.0911686107openalex-snapshot
Anonymization of electronic medical records for validating genome-wide association studies
inferredcites →https://doi.org/10.1081/e-ept4-120050267openalex-snapshot
European Medicines Agency (EMA)
inferredcites →https://doi.org/10.1093/bib/bbac440openalex-snapshot
Open tools for quantitative anonymization of tabular phenotype data: literature review
inferredcites →https://doi.org/10.1093/jamia/ocad021openalex-snapshot
Managing re-identification risks while providing access to the All of Us research program
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R-U policy frontiers for health data de-identification
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Project Data Sphere to Make Cancer Clinical Trial Data Publicly Available
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The German Chronic Kidney Disease (GCKD) study: design and methods
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Disease burden and risk profile in referred patients with moderate chronic kidney disease: composition of the German Chronic Kidney Disease (GCKD) cohort
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Article 68 European Data Protection Board
inferredcites →https://doi.org/10.1109/jbhi.2017.2676880openalex-snapshot
A Scalable and Pragmatic Method for the Safe Sharing of High-Quality Health Data
inferredcites →https://doi.org/10.1111/j.1467-842x.2001.tb00294.xopenalex-snapshot
How can I deal with missing data in my study?
inferredcites →https://doi.org/10.1136/bmj.g4073openalex-snapshot
European Medicines Agency changes policy on clinical trial data publication
inferredcites →https://doi.org/10.1136/bmj.h1139openalex-snapshot
Anonymising and sharing individual patient data
inferredcites →https://doi.org/10.1136/bmj.k400openalex-snapshot
Data sharing and reanalysis of randomized controlled trials in leading biomedical journals with a full data sharing policy: survey of studies published inThe BMJandPLOS Medicine
inferredcites →https://doi.org/10.1142/s0218488502001648openalex-snapshot
k-ANONYMITY: A MODEL FOR PROTECTING PRIVACY
inferredcites →https://doi.org/10.1145/775047.775089openalex-snapshot
Transforming data to satisfy privacy constraints
inferredcites →https://doi.org/10.1158/1557-3265.adi21-pr-09openalex-snapshot
Abstract PR-09: Genetic risk scores for breast cancer based on machine learning analysis of chromosomal-scale length variation
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Multiple imputation: a primer
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A systematic review of barriers to data sharing in public health
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Responsible data sharing in international health research: a systematic review of principles and norms
inferredcites →https://doi.org/10.1186/s12911-017-0499-0openalex-snapshot
Utility-preserving anonymization for health data publishing
inferredcites →https://doi.org/10.1186/s13063-017-2382-9openalex-snapshot
Data sharing in clinical trials – practical guidance on anonymising trial datasets
inferredcites →https://doi.org/10.1197/jamia.m2273openalex-snapshot
Toward a National Framework for the Secondary Use of Health Data: An American Medical Informatics Association White Paper
inferredcites →https://doi.org/10.1197/jamia.m3144openalex-snapshot
A Globally Optimal k-Anonymity Method for the De-Identification of Health Data
inferredcites →https://doi.org/10.1198/000313006x124640openalex-snapshot
A Framework for Evaluating the Utility of Data Altered to Protect Confidentiality
inferredcites →https://doi.org/10.1371/journal.pmed.1003844openalex-snapshot
Medical journal requirements for clinical trial data sharing: Ripe for improvement
inferredcites →https://doi.org/10.1371/journal.pone.0028071openalex-snapshot
A Systematic Review of Re-Identification Attacks on Health Data
inferredcites →https://doi.org/10.2165/00128413-200615320-00045openalex-snapshot
The UK Medicines and Healthcare products Regulatory Agency (MHRA) has launched an initiative with academia
inferredcites →https://doi.org/10.2196/13484openalex-snapshot
Use and Understanding of Anonymization and De-Identification in the Biomedical Literature: Scoping Review
inferredcites →https://doi.org/10.2196/29871openalex-snapshot
Data Anonymization for Pervasive Health Care: Systematic Literature Mapping Study
inferredcites →https://doi.org/10.2196/37756openalex-snapshot
Twenty Years of the Health Insurance Portability and Accountability Act Safe Harbor Provision: Unsolved Challenges and Ways Forward
inferredcites →https://doi.org/10.31228/osf.io/mu2kfopenalex-snapshot
A Right to Reasonable Inferences: Re-Thinking Data Protection Law in the Age of Big Data and AI
inferredcites →https://doi.org/10.3233/978-1-61499-678-1-312openalex-snapshot
A Generic Method for Assessing the Quality of De-Identified Health Data
inferredcites →https://doi.org/10.3233/shti230058openalex-snapshot
Utility-Preserving Anonymization in a Real-World Scenario: Evidence from the German Chronic Kidney Disease (GCKD) Study
inferredcites →https://doi.org/10.3945/ajcn.2008.26698openalex-snapshot
Estimates of excess deaths associated with body mass index and other anthropometric variables
inferredcites →https://doi.org/10.5281/zenodo.7978629openalex-snapshot
pilgraml/UseCaseSpecificAnonymization: Published generalization hierarchies
inferredcites →https://doi.org/10.9778/cmajo.20200303openalex-snapshot
Data-sharing practices in publications funded by the Canadian Institutes of Health Research: a descriptive analysis
What points at this work
Incoming claims: where this work appears in other papers’ reference lists and arguments.
inferred← citeshttps://doi.org/10.1007/978-3-032-31998-2_22openalex-snapshot
A Holistic Framework for Privacy-Preserving Data Publishing with Synthetic Data and k-l Diversity
inferred← citeshttps://doi.org/10.1007/978-981-96-4285-4_34openalex-snapshot
Privacy Challenges in Genomic Data: A Scoping Review of Risks, Mitigation Strategies, and Research Gaps
inferred← citeshttps://doi.org/10.1007/s10278-026-02047-2openalex-snapshot
Advancing Data Privacy Under GDPR: A Bayesian Approach to Structured Risk Quantification in Medical DICOM Data
inferred← citeshttps://doi.org/10.1007/s10462-025-11353-0openalex-snapshot
Unlocking the potential of deep learning in brain stroke prognosis: a systematic literature review
inferred← citeshttps://doi.org/10.1007/s41060-026-01144-3openalex-snapshot
Quality metrics for Privacy-Preserving Data Mining: a systematic review, phase-based classification, and critical synthesis
inferred← citeshttps://doi.org/10.1016/j.compbiomed.2025.110738openalex-snapshot
Phantom Anonymization: Adversarial testing for membership inference risks in anonymized health data
inferred← citeshttps://doi.org/10.1038/s41746-026-02622-5openalex-snapshot
A case study comparing anonymized and synthetic health insurance claims data for medication safety assessments
inferred← citeshttps://doi.org/10.1093/haschl/qxaf210openalex-snapshot
A real-world data challenge: guidance for aligning data privacy compliance and fit-for-purpose usability
inferred← citeshttps://doi.org/10.1093/jamia/ocaf169openalex-snapshot
Should we synthesize more than we need: impact of synthetic data generation for high-dimensional cross-sectional medical data
inferred← citeshttps://doi.org/10.1109/icecet63943.2025.11472114openalex-snapshot
Learning rPPG without Facial Identity
inferred← citeshttps://doi.org/10.1145/3719027.3765139openalex-snapshot
Exposing Privacy Risks in Anonymizing Clinical Data: Combinatorial Refinement Attacks on k -Anonymity Without Auxiliary Information
inferred← citeshttps://doi.org/10.1177/17407745251356423openalex-snapshot
Evaluating re-identification risks scores in publicly available clinical trial datasets: Insights and implications
inferred← citeshttps://doi.org/10.1186/s12911-025-02959-zopenalex-snapshot
Parallel privacy preservation through partitioning (P4): a scalable data anonymization algorithm for health data
inferred← citeshttps://doi.org/10.1371/journal.pone.0342692openalex-snapshot
Assessing Local Differential Privacy for Compliance with the Personal Data Protection Law in Integrated Data Systems
inferred← citeshttps://doi.org/10.2196/97661openalex-snapshot
Quantifying the Impact of Anonymization-Induced Clinical Data Quality Loss: Methodological Quantitative Case Study Using Primary Diagnosis Codes and Hospital Length of Stay
inferred← citeshttps://doi.org/10.2196/preprints.97661openalex-snapshot
Quantifying the Impact of Anonymization-Induced Clinical Data Quality Loss: A Methodological Study Using Primary Diagnosis Codes and Hospital Length of Stay (Preprint)
inferred← citeshttps://doi.org/10.5753/sbcas.2026.21679openalex-snapshot
Privacy without Loss of Utility: Evaluation of De-identification Techniques in Deep Learning for Intensive Care Units
inferred← citeshttps://doi.org/10.71451/istaer2539openalex-snapshot
Privacy-Utility Tradeoff: Studying the Boundaries of Anonymization in Health Data Visualization Design
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