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Rule-based Cervical Spine Defect Classification Using Medical Narratives.
Deng, Yihan; Groll, Mathias Jacob; Denecke, Kerstin.
Afiliação
  • Deng Y; Innovation Center of Computer Assisted Surgery, University of Leipzig, Germany.
  • Groll MJ; Nourosurgical Department, University Hospital Leipzig, Germany.
  • Denecke K; Innovation Center of Computer Assisted Surgery, University of Leipzig, Germany.
Stud Health Technol Inform ; 216: 1038, 2015.
Article em En | MEDLINE | ID: mdl-26262337
Classifying the defects occurring at the cervical spine provides the basis for surgical treatment planning and therapy recommendation. This process requires evidence from patient records. Further, the degree of a defect needs to be encoded in a standardized from to facilitate data exchange and multimodal interoperability. In this paper, a concept for automatic defect classification based on information extracted from textual data of patient records is presented. In a retrospective study, the classifier is applied to clinical documents and the classification results are evaluated.
Assuntos
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Base de dados: MEDLINE Assunto principal: Estenose Espinal / Algoritmos / Processamento de Linguagem Natural / Diagnóstico por Computador / Sistemas de Apoio a Decisões Clínicas / Terminologia como Assunto Tipo de estudo: Diagnostic_studies / Guideline / Observational_studies / Prognostic_studies / Qualitative_research Limite: Humans Idioma: En Ano de publicação: 2015 Tipo de documento: Article
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Base de dados: MEDLINE Assunto principal: Estenose Espinal / Algoritmos / Processamento de Linguagem Natural / Diagnóstico por Computador / Sistemas de Apoio a Decisões Clínicas / Terminologia como Assunto Tipo de estudo: Diagnostic_studies / Guideline / Observational_studies / Prognostic_studies / Qualitative_research Limite: Humans Idioma: En Ano de publicação: 2015 Tipo de documento: Article