A Framework for Extracting, and Validating Named-Entities to Integrate Openehr Using the Example of Free Text Molecular Genetic Findings...20th World Congress on Medical and Health Informatics (MEDINFO), August 9-13, 2025, Taipei, Taiwan
Processing and extracting information from unstructured texts written by physicians in Hospitals is still an open problem. There is no efficient solution that ensures the reliability of the extracted information without any human intervention. Many factors, like the low availability of documents in...
| Publicado en: | Studies in Health Technology & Informatics Vol. 329; pp. 708 - 713 |
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| Autores principales: | , , , , , |
| Formato: | proceedings research tables/charts Journal Article |
| Publicado: |
Sage Publications Inc.
2025
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| Acceso en línea: | Ver este registro en EBSCOhost |
| fields | @attributes: recordID: 1 pdfLink: plink: https://search.ebscohost.com/login.aspx?direct=true&db=ccm&AN=187334950&site=ehost-live header: @attributes: shortDbName: ccm uiTerm: 187334950 longDbName: CINAHL Complete uiTag: AN controlInfo: bkinfo: dissinfo: jinfo: jid: 09269630 U1V jtl: Studies in Health Technology & Informatics issn: 09269630 maglogo: N pubinfo: dt: 2025 vid: 329 pid: 344 pub: Sage Publications Inc. place: Thousand Oaks, California artinfo: ui: 187334950 187334950 187334950 10.3233/SHTI250932 187334950 ppf: 708 ppct: 5 formats: tig: atl: A Framework for Extracting, and Validating Named-Entities to Integrate Openehr Using the Example of Free Text Molecular Genetic Findings...20th World Congress on Medical and Health Informatics (MEDINFO), August 9-13, 2025, Taipei, Taiwan aug: au: LADAS, Nektarios FRANZ, Stefan SCHIECK, Maximilian REHBERG, Alina MARSCHOLLEK, Michael GIETZELT, Matthias affil: Peter L. Reichertz Institute for Medical Informatics, TU Braunschweig and Hannover Medical School, Germany sug: subj: Electronic Health Records Natural Language Processing Genetic Variation Information Storage Information Retrieval Data Quality Evaluation Congresses and Conferences Taiwan Taiwan Descriptive Statistics Database Management Software Data Analysis, Computer Assisted ab: Processing and extracting information from unstructured texts written by physicians in Hospitals is still an open problem. There is no efficient solution that ensures the reliability of the extracted information without any human intervention. Many factors, like the low availability of documents in the training phase, patient-sensitive information, and the complexity of the written texts can impact the results. Through our scientific journey, to integrate unstructured texts in openEHR, we have developed tools that together provide a complete process to efficiently extract, validate and integrate data in openEHR. As a use case, we demonstrate the free written texts in molecular genetic findings to present our results. The validation of the pipeline resulted in an F-score of 0.98. pubtype: Academic Journal doctype: proceedings research tables/charts Journal Article ougenre: Article language: English refInfo: holdings: @attributes: islocal: N |
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