A globally optimal k-anonymity method for the de-identification of health data - Wikidata - wikimedia - TriplyDB

A globally optimal k-anonymity method for the de-identification of health data

A globally optimal k-anonymity method for the de-identification of health data

http://www.wikidata.org/entity/Q33476731

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Ensuring Confidentiality of Geocoded Health Data: Assessing Geographic Masking Strategies for Individual-Level Data Privacy technology to support data sharing for comparative effectiveness research: a systematic review Identifiability in biobanks: models, measures, and mitigation strategies R-U policy frontiers for health data de-identification Anonymising and sharing individual patient data DeID - a data sharing tool for neuroimaging studies Size matters: how population size influences genotype-phenotype association studies in anonymized data Development and evaluation of a de-identification procedure for a case register sourced from mental health electronic records A collaborative framework for Distributed Privacy-Preserving Support Vector Machine learning A Protocol for the secure linking of registries for HPV surveillance De-identification methods for open health data: the case of the Heritage Health Prize claims dataset Trends in biomedical informatics: most cited topics from recent years A systematic review of re-identification attacks on health data Physician privacy concerns when disclosing patient data for public health purposes during a pandemic influenza outbreak Never too old for anonymity: a statistical standard for demographic data sharing via the HIPAA Privacy Rule De-identifying a public use microdata file from the Canadian national discharge abstract database Privacy and anonymity challenges when collecting data for public health purposes.Protecting privacy in a clinical data warehouse.ARX--A Comprehensive Tool for Anonymizing Biomedical Data.Efficient and effective pruning strategies for health data de-identification.Evaluating the Risk of Re-identification of Patients from Hospital Prescription Records Data-driven approach for creating synthetic electronic medical records.Utility-preserving anonymization for health data publishing Evaluating the risk of patient re-identification from adverse drug event reports.New threats to health data privacy Building public trust in uses of Health Insurance Portability and Accountability Act de-identified data.Estimating the re-identification risk of clinical data sets Enabling genomic-phenomic association discovery without sacrificing anonymity.Methods for the de-identification of electronic health records for genomic research Attribute Utility Motivated k-anonymization of datasets to support the heterogeneous needs of biomedical researchers.A Privacy Preservation Model for Health-Related Social Networking Sites Reducing patient re-identification risk for laboratory results within research datasets.Lessons Learned from Development of De-identification System for Biomedical Research in a Korean Tertiary Hospital Anonymization of longitudinal electronic medical records.Meeting the privacy requirements for the development of a multi-centre patient registry in Canada: the Rick Hansen Spinal Cord Injury Registry.A review of evidence on consent bias in research.Barbarians at the Gate: Consumer-Driven Health Data Commons and the Transformation of Citizen Science.Geolocation with respect to personal privacy for the Allergy Diary app - a MASK study MASK 2017: ARIA digitally-enabled, integrated, person-centred care for rhinitis and asthma multimorbidity using real-world-evidence Protecting Anonymity in Data-Driven Biomedical Science

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A globally optimal k-anonymity method for the de-identification of health data

http://www.wikidata.org/entity/Q33476731

description

2009 nî lūn-bûn

@nan

2009 թուականի Յունիսին հրատարակուած գիտական յօդուած

@hyw

2009 թվականի հունիսին հրատարակված գիտական հոդված

@hy

2009年の論文

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2009年論文

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2009年論文

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2009年論文

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2009年論文

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2009年論文

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2009年论文

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name

A globally optimal k-anonymity method for the de-identification of health data

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A globally optimal k-anonymity method for the de-identification of health data

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type

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A globally optimal k-anonymity method for the de-identification of health data

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A globally optimal k-anonymity method for the de-identification of health data

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prefLabel

A globally optimal k-anonymity method for the de-identification of health data

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A globally optimal k-anonymity method for the de-identification of health data

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Journal of the American Medical Informatics Association

P1476

A globally optimal k-anonymity method for the de-identification of health data

@en

P2093

Daniel Amyot

http://www.w3.org/2001/XMLSchema#string

Elise Cogo

http://www.w3.org/2001/XMLSchema#string

Elizabeth Jonker

http://www.w3.org/2001/XMLSchema#string

Fida Kamal Dankar

http://www.w3.org/2001/XMLSchema#string

Jean-Pierre Corriveau

http://www.w3.org/2001/XMLSchema#string

Jim Bottomley

http://www.w3.org/2001/XMLSchema#string

Khaled El Emam

http://www.w3.org/2001/XMLSchema#string

Mark Walker

http://www.w3.org/2001/XMLSchema#string

Regis Vaillancourt

http://www.w3.org/2001/XMLSchema#string

Romeo Issa

http://www.w3.org/2001/XMLSchema#string

P2860

Evaluating predictors of geographic area population size cut-offs to manage re-identification risk

Learning from experience: privacy and the secondary use of data in health research.

Evaluating the Risk of Re-identification of Patients from Hospital Prescription Records

Health Insurance Portability and Accountability Act Privacy rule causes ongoing concerns among clinicians and researchers.

Evaluating common de-identification heuristics for personal health information.

Health Insurance Portability Accountability Act (HIPAA) regulations: effect on medical record research.

HIPAA--Implications for research.

The Health Insurance Portability and Accountability Act of 1996 (HIPAA) privacy rule: implications for clinical research.

HIPAA and research: how have the first two years gone?

Guaranteeing anonymity when sharing medical data, the Datafly System.

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670-682

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scholarly article

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10.1197/JAMIA.M3144

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P433

5

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P478

16

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2009-06-30T00:00:00Z

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19567795

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P932

2744718

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