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Automated semantic indexing of imaging reports to support retrieval of medical images in the multimedia electronic medical record.

机译:成像报告的自动语义索引支持在多媒体电子病历中检索医学图像。

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This paper describes preliminary work evaluating automated semantic indexing of radiology imaging reports to represent images stored in the Image Engine multimedia medical record system at the University of Pittsburgh Medical Center. The authors used the SAPHIRE indexing system to automatically identify important biomedical concepts within radiology reports and represent these concepts with terms from the 1998 edition of the U.S. National Library of Medicine's Unified Medical Language System (UMLS) Metathesaurus. This automated UMLS indexing was then compared with manual UMLS indexing of the same reports. Human indexing identified appropriate UMLS Metathesaurus descriptors for 81% of the important biomedical concepts contained in the report set. SAPHIRE automatically identified UMLS Metathesaurus descriptors for 64% of the important biomedical concepts contained in the report set. The overall conclusions of this pilot study were that the UMLS metathesaurus provided adequate coverage of the majority of the important concepts contained within the radiology report test set and that SAPHIRE could automatically identify and translate almost two thirds of these concepts into appropriate UMLS descriptors. Further work is required to improve both the recall and precision of this automated concept extraction process.
机译:本文介绍了评估放射影像报告自动语义索引以代表存储在匹兹堡大学医学中心影像引擎多媒体病历系统中的影像的初步工作。作者使用SAPHIRE索引系统自动识别放射学报告中的重要生物医学概念,并用1998年美国国家医学图书馆统一医学语言系统(UMLS)元同义词库的术语表示这些概念。然后将这种自动UMLS索引与相同报表的手动UMLS索引进行比较。人工索引为报告集中所包含的重要生物医学概念的81%确定了适当的UMLS元同义词叙词。 SAPHIRE自动识别报告集中包含的64%的重要生物医学概念的UMLS Metathesaurus描述符。这项初步研究的总体结论是,UMLS词库对放射学报告测试集中包含的大多数重要概念提供了足够的覆盖范围,并且SAPHIRE可以自动识别并将这些概念的近三分之二转换为合适的UMLS描述符。需要进一步的工作来提高这种自动化概念提取过程的召回率和精度。

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