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AHD2FHIR: A Tool for Mapping of Natural Language Annotations to Fast Healthcare Interoperability Resources - A Technical Case Report.
Scheible, Raphael; Caliskan, Deniz; Fischer, Patrick; Thomczyk, Fabian; Zabka, Susanne; Schneider, Henning; Boeker, Martin; Schulz, Stefan; Prokosch, Hans-Ulrich; Gulden, Christian.
Afiliação
  • Scheible R; Institute of Medical Informatics, Statistics and Epidemiology, University Hospital rechts der Isar, Technical University of Munich, Munich, Germany.
  • Caliskan D; Institute of Medical Biometry and Statistics, Medical Center, Faculty of Medicine, University of Freiburg, Freiburg, Germany.
  • Fischer P; Medical Center for Information and Communication Technology, University Hospital Erlangen, Erlangen, Germany.
  • Thomczyk F; Institute of Medical Informatics, Faculty of Medicine, Justus-Liebig-University Giessen, Giessen, Germany.
  • Zabka S; Institute of Medical Biometry and Statistics, Medical Center, Faculty of Medicine, University of Freiburg, Freiburg, Germany.
  • Schneider H; Institute of Medical Biometry and Statistics, Medical Center, Faculty of Medicine, University of Freiburg, Freiburg, Germany.
  • Boeker M; Institute of Medical Informatics, Faculty of Medicine, Justus-Liebig-University Giessen, Giessen, Germany.
  • Schulz S; Institute of Medical Informatics, Statistics and Epidemiology, University Hospital rechts der Isar, Technical University of Munich, Munich, Germany.
  • Prokosch HU; Institute of Medical Biometry and Statistics, Medical Center, Faculty of Medicine, University of Freiburg, Freiburg, Germany.
  • Gulden C; Averbis GmbH, Freiburg, Germany.
Stud Health Technol Inform ; 290: 32-36, 2022 Jun 06.
Article em En | MEDLINE | ID: mdl-35672965
ABSTRACT
A significant portion of data in Electronic Health Records is only available as unstructured text, such as surgical or finding reports, clinical notes and discharge summaries. To use this data for secondary purposes, natural language processing (NLP) tools are required to extract structured information. Furthermore, for interoperable use, harmonization of the data is necessary. HL7 Fast Healthcare Interoperability Resources (FHIR), an emerging standard for exchanging healthcare data, defines such a structured format. For German-language medical NLP, the tool Averbis Health Discovery (AHD) represents a comprehensive solution. AHD offers a proprietary REST interface for text analysis pipelines. To build a bridge between FHIR and this interface, we created a service that translates the communication around AHD from and to FHIR. The application is available under an open source license.
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Texto completo: 1 Base de dados: MEDLINE Assunto principal: Processamento de Linguagem Natural / Registros Eletrônicos de Saúde Limite: Humans Idioma: En Revista: Stud Health Technol Inform Assunto da revista: INFORMATICA MEDICA / PESQUISA EM SERVICOS DE SAUDE Ano de publicação: 2022 Tipo de documento: Article País de afiliação: Alemanha

Texto completo: 1 Base de dados: MEDLINE Assunto principal: Processamento de Linguagem Natural / Registros Eletrônicos de Saúde Limite: Humans Idioma: En Revista: Stud Health Technol Inform Assunto da revista: INFORMATICA MEDICA / PESQUISA EM SERVICOS DE SAUDE Ano de publicação: 2022 Tipo de documento: Article País de afiliação: Alemanha