Automatic de-identification of textual documents in the electronic health record: a review of recent research. - Wikidata - awgldk - TriplyDB

Automatic de-identification of textual documents in the electronic health record: a review of recent research.

Automatic de-identification of textual documents in the electronic health record: a review of recent research.

http://www.wikidata.org/entity/Q33647432

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Extracting information from the text of electronic medical records to improve case detection: a systematic review Mining electronic health records: towards better research applications and clinical care Automated systems for the de-identification of longitudinal clinical narratives: Overview of 2014 i2b2/UTHealth shared task Track 1 Genomics and privacy: implications of the new reality of closed data for the field What evidence is there for a delay in diagnostic coding of RA in UK general practice records? An observational study of free text Optimizing annotation resources for natural language de-identification via a game theoretic framework CRFs based de-identification of medical records Automatic de-identification of electronic medical records using token-level and character-level conditional random fields Recent Advances in Clinical Natural Language Processing in Support of Semantic Analysis The pattern of name tokens in narrative clinical text and a comparison of five systems for redacting them Development and evaluation of a de-identification procedure for a case register sourced from mental health electronic records SHARE: system design and case studies for statistical health information release BoB, a best-of-breed automated text de-identification system for VHA clinical documents Generalizability and comparison of automatic clinical text de-identification methods and resources Mining the pharmacogenomics literature--a survey of the state of the art Preparing an annotated gold standard corpus to share with extramural investigators for de-identification research Genetic data sharing and privacy.Piloting a deceased subject integrated data repository and protecting privacy of relatives.Advancing the Use of Administrative Data for Emergency Department Diagnostic Imaging Research.Screening Consolidated Clinical Document Architecture (CCDA) Documents for Sensitive Data Using a Rule-Based Decision Support System.Effect and maintenance of the SLIMMER diabetes prevention lifestyle intervention in Dutch primary healthcare: a randomised controlled trial A context-blocks model for identifying clinical relationships in patient records.Evaluating current automatic de-identification methods with Veteran's health administration clinical documents.De-identification of clinical narratives through writing complexity measures.Managing protected health information in distributed research network environments: automated review to facilitate collaboration.Improved de-identification of physician notes through integrative modeling of both public and private medical text.Methods for the de-identification of electronic health records for genomic research De-identification of Address, Date, and Alphanumeric Identifiers in Narrative Clinical Reports.Strategies for maintaining patient privacy in i2b2.Attribute Utility Motivated k-anonymization of datasets to support the heterogeneous needs of biomedical researchers.Challenges and Insights in Using HIPAA Privacy Rule for Clinical Text Annotation P2P watch: personal health information detection in peer-to-peer file-sharing networks Learning to identify Protected Health Information by integrating knowledge- and data-driven algorithms: A case study on psychiatric evaluation notes.Evaluation of PHI Hunter in Natural Language Processing Research.Anonymisation of geographical distance matrices via Lipschitz embedding Large-scale evaluation of automated clinical note de-identification and its impact on information extraction.Hiding in plain sight: use of realistic surrogates to reduce exposure of protected health information in clinical text.Lessons Learned from Development of De-identification System for Biomedical Research in a Korean Tertiary Hospital Location bias of identifiers in clinical narratives.Is the Juice Worth the Squeeze? Costs and Benefits of Multiple Human Annotators for Clinical Text De-identification.

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Automatic de-identification of textual documents in the electronic health record: a review of recent research.

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2010 nî lūn-bûn

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2010 թուականի Օգոստոսին հրատարակուած գիտական յօդուած

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2010 թվականի օգոստոսին հրատարակված գիտական հոդված

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2010年の論文

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Automated de-identification of free-text medical records.

Concept-match medical data scrubbing. How pathology text can be used in research.

Development and evaluation of an open source software tool for deidentification of pathology reports.

Extracting information from textual documents in the electronic health record: a review of recent research.

Recognizing obesity and comorbidities in sparse data.

Evaluating the state-of-the-art in automatic de-identification.

Replacing personally-identifying information in medical records, the Scrub system

A broad-coverage natural language processing system.

Medical document anonymization with a semantic lexicon.

A successful technique for removing names in pathology reports using an augmented search and replace method.

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