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De-Identification of Medical Narrative Data
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2017
Year
Accountability ActEngineeringNarrative SummarizationCorpus LinguisticsText MiningNarrative RepresentationNatural Language ProcessingData ScienceMedical DocumentsData IntegrationMedical Narrative DataLanguage StudiesPublic HealthBiomedical Text MiningContent AnalysisData ManagementNarrative ExtractionElectronic Health RecordMedical Language ProcessingInformation ExtractionHealth DataMedical PrivacyMedicineLinguisticsHealth Informatics
Maintaining data security and privacy in an era of cybersecurity is a challenge. The enormous and rapidly growing amount of health-related data available today raises numerous questions about data collection, storage, analysis, comparability and interoperability but also about data protection. The US Health Portability and Accountability Act (HIPAA) of 1996 provides a legal framework and a guidance for using and disclosing health data. Practically, the approach proposed by HIPAA is the de-identification of medical documents by removing certain Protected Health Information (PHI). In this work, a rule-based method for the de-identification of French free-text medical data using Natural Language Processing (NLP) tools will be presented.