OcrV1, Main, Exploration, bibRecord, 000104

De-identification of unstructured paper-based health records for privacy-preserving secondary use.

Identifieur interne : 000104 ( Main/Exploration ); précédent : 000103; suivant : 000105

De-identification of unstructured paper-based health records for privacy-preserving secondary use.

Auteurs : Stefan Fenz [Autriche] ; Johannes Heurix ; Thomas Neubauer ; Antonio Rella

Source :

Journal of medical engineering & technology [ 1464-522X ] ; 2014.

RBID : pubmed:24841844

English descriptors

KwdEn :
- Artificial Intelligence, Confidentiality, Forms and Records Control (methods), Health Records, Personal, Image Processing, Computer-Assisted, Information Storage and Retrieval (methods), Paper, Privacy.
MESH :
- methods : Forms and Records Control, Information Storage and Retrieval.
- Artificial Intelligence, Confidentiality, Health Records, Personal, Image Processing, Computer-Assisted, Paper, Privacy.

Abstract

Abstract Whenever personal data is processed, privacy is a serious issue. Especially in the document-centric e-health area, the patients' privacy must be preserved in order to prevent any negative repercussions for the patient. Clinical research, for example, demands structured health records to carry out efficient clinical trials, whereas legislation (e.g. HIPAA) regulates that only de-identified health records may be used for research. However, unstructured and often paper-based data dominates information technology, especially in the healthcare sector. Existing approaches are geared towards data in English-language documents only and have not been designed to handle the recognition of erroneous personal data which is the result of the OCR-based digitization of paper-based health records.

DOI: 10.3109/03091902.2014.913080
PubMed: 24841844

Affiliations:

Le document en format XML

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<affiliation wicri:level="3"><nlm:affiliation>Vienna University of Technology, Institute of Software Technology and Interactive Systems , Favoritenstrasse 9-11, 1040 Vienna , Austria.</nlm:affiliation>
<country xml:lang="fr">Autriche</country>
<wicri:regionArea>Vienna University of Technology, Institute of Software Technology and Interactive Systems , Favoritenstrasse 9-11, 1040 Vienna </wicri:regionArea>
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<author><name sortKey="Rella, Antonio" sort="Rella, Antonio" uniqKey="Rella A" first="Antonio" last="Rella">Antonio Rella</name>
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<series><title level="j">Journal of medical engineering & technology</title>
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<term>Privacy</term>
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<front><div type="abstract" xml:lang="en">Abstract Whenever personal data is processed, privacy is a serious issue. Especially in the document-centric e-health area, the patients' privacy must be preserved in order to prevent any negative repercussions for the patient. Clinical research, for example, demands structured health records to carry out efficient clinical trials, whereas legislation (e.g. HIPAA) regulates that only de-identified health records may be used for research. However, unstructured and often paper-based data dominates information technology, especially in the healthcare sector. Existing approaches are geared towards data in English-language documents only and have not been designed to handle the recognition of erroneous personal data which is the result of the OCR-based digitization of paper-based health records.</div>
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<name sortKey="Rella, Antonio" sort="Rella, Antonio" uniqKey="Rella A" first="Antonio" last="Rella">Antonio Rella</name>
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Serveur d'exploration sur l'OCR

De-identification of unstructured paper-based health records for privacy-preserving secondary use.

De-identification of unstructured paper-based health records for privacy-preserving secondary use.

Source :

English descriptors

Abstract

Links toward previous steps (curation, corpus...)

Le document en format XML

Pour manipuler ce document sous Unix (Dilib)

Pour mettre un lien sur cette page dans le réseau Wicri

Pour générer des pages wiki

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