Guaranteeing anonymity when sharing medical data, the Datafly System.
about
Automated de-identification of free-text medical records.iDASH: integrating data for analysis, anonymization, and sharingIndivo: a personally controlled health record for health information exchange and communicationHealth information identification and de-identification toolkitTechnical and policy approaches to balancing patient privacy and data sharing in clinical and translational researchIntegration and beyond: linking information from disparate sources and into workflowA context-sensitive approach to anonymizing spatial surveillance data: impact on outbreak detectionA secure protocol to distribute unlinkable health data.Privacy preserving data publishing of categorical data through k-anonymity and feature selection.Disambiguation data: extracting information from anonymized sources.Development and evaluation of an open source software tool for deidentification of pathology reports.A globally optimal k-anonymity method for the de-identification of health dataA method for managing re-identification risk from small geographic areas in Canada.Multicenter patient records research: security policies and tools.Directions for clinical research and genomic research into the next decade: implications for informatics.Medicine and the InternetImplementing syndromic surveillance: a practical guide informed by the early experience.Building public trust in uses of Health Insurance Portability and Accountability Act de-identified data.A systems overview of the Electronic Surveillance System for the Early Notification of Community-Based Epidemics (ESSENCE II).The contributions of biomedical informatics to the fight against bioterrorism.A successful technique for removing names in pathology reports using an augmented search and replace method.A proposed key escrow system for secure patient information disclosure in biomedical research databases.A model for expanded public health reporting in the context of HIPAA.A software tool for removing patient identifying information from clinical documents.Bioinformatics and clinical informatics: the imperative to collaborate.Effects of Data Anonymization by Cell Suppression on Descriptive Statistics and Predictive Modeling Performance.Disambiguation Data: Extracting Information from Anonymized Sources.
P2860
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P2860
Guaranteeing anonymity when sharing medical data, the Datafly System.
description
1997 nî lūn-bûn
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1997年の論文
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1997年学术文章
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1997年学术文章
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1997年学术文章
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1997年学术文章
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1997年学术文章
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1997年學術文章
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1997年學術文章
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name
Guaranteeing anonymity when sharing medical data, the Datafly System.
@ast
Guaranteeing anonymity when sharing medical data, the Datafly System.
@en
type
label
Guaranteeing anonymity when sharing medical data, the Datafly System.
@ast
Guaranteeing anonymity when sharing medical data, the Datafly System.
@en
prefLabel
Guaranteeing anonymity when sharing medical data, the Datafly System.
@ast
Guaranteeing anonymity when sharing medical data, the Datafly System.
@en
P1476
Guaranteeing anonymity when sharing medical data, the Datafly System
@en
P2093
P577
1997-01-01T00:00:00Z