J Am Med Inform Assoc - Comparison of a semi-automatic annotation tool and a natural language processing application for the generation of clinical statement entries.

Tópicos

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{ age(1611) year(1155) adult(843) }
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{ health(1844) social(1437) communiti(874) }
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{ drug(1928) target(777) effect(648) }
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Resumo

CKGROUND AND OBJECTIVE: Electronic medical records with encoded entries should enhance the semantic interoperability of document exchange. However, it remains a challenge to encode the narrative concept and to transform the coded concepts into a standard entry-level document. This study aimed to use a novel approach for the generation of entry-level interoperable clinical documents.METHODS: Using HL7 clinical document architecture (CDA) as the example, we developed three pipelines to generate entry-level CDA documents. The first approach was a semi-automatic annotation pipeline (SAAP), the second was a natural language processing (NLP) pipeline, and the third merged the above two pipelines. We randomly selected 50 test documents from the i2b2 corpora to evaluate the performance of the three pipelines.RESULTS: The 50 randomly selected test documents contained 9365 words, including 588 Observation terms and 123 Procedure terms. For the Observation terms, the merged pipeline had a significantly higher F-measure than the NLP pipeline (0.89 vs 0.80, p<0.0001), but a similar F-measure to that of the SAAP (0.89 vs 0.87). For the Procedure terms, the F-measure was not significantly different among the three pipelines.CONCLUSIONS: The combination of a semi-automatic annotation approach and the NLP application seems to be a solution for generating entry-level interoperable clinical documents.

Resumo Limpo

ckground object electron medic record encod entri enhanc semant interoper document exchang howev remain challeng encod narrat concept transform code concept standard entrylevel document studi aim use novel approach generat entrylevel interoper clinic documentsmethod use hl clinic document architectur cda exampl develop three pipelin generat entrylevel cda document first approach semiautomat annot pipelin saap second natur languag process nlp pipelin third merg two pipelin random select test document ib corpora evalu perform three pipelinesresult random select test document contain word includ observ term procedur term observ term merg pipelin signific higher fmeasur nlp pipelin vs p similar fmeasur saap vs procedur term fmeasur signific differ among three pipelinesconclus combin semiautomat annot approach nlp applic seem solut generat entrylevel interoper clinic document

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