A GENERAL NATURAL-LANGUAGE TEXT PROCESSOR FOR CLINICAL RADIOLOGY
A GENERAL NATURAL-LANGUAGE TEXT PROCESSOR FOR CLINICAL RADIOLOGY
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DOI：
10.1136/jamia.1994.95236146
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发表时间：
1994-03-01
影响因子：
6.4
通讯作者：
JOHNSON, SB
中科院分区：
文献类型：
--
作者：
FRIEDMAN, C;ALDERSON, PO;JOHNSON, SB
目的：开发一个通用的自然语言处理器，识别临床信息的叙述性报告，并将该信息映射到一个结构化的表示包含clinicalterms.Design：自然语言处理器提供了三个阶段的处理，所有。这些知识来源于不同的知识。第一阶段执行解析。它通过使用定义语义模式和目标形式的语法来识别文本的结构。第二个阶段，正则化，通过多词短语的组合映射来对初始目标结构中的术语进行正则化。第三个阶段，编码，将术语映射到受控词汇表。放射学是处理器的测试域，目标结构是表示该域中临床信息的正式模型。测量：230份放射学报告的印象部分由处理器编码。四种疾病的发生所得到的数据库的自动查询的结果进行了比较，一个小组的三个医生的分析，以确定召回率和precision.Results：没有特定的四种疾病的培训，召回率和精度的系统（处理器和查询生成器的综合效果）分别为70%和87%。查询组件的训练将召回率提高到85%，而不改变精度。
Objective: Development of a general natural-language processor that identifies clinical information in narrative reports and maps that information into a structured representation containing clinical terms.Design: The natural-language processor provides three phases of processing, all. of which are driven by different knowledge sources. The first phase performs the parsing. It identifies the structure of the text through use of a grammar that defines semantic patterns and a target form. The second phase, regularization, standardizes the terms in the initial target structure via a compositional mapping of multi-word phrases. The third phase, encoding, maps the terms to a controlled vocabulary. Radiology is the test domain for the processor and the target structure is a formal model for representing clinical information in that domain.Measurements: The impression sections of 230 radiology reports were encoded by the processor. Results of an automated query of the resultant database for the occurrences of four diseases were compared with the analysis of a panel of three physicians to determine recall and precision.Results: Without training specific to the four diseases, recall and precision of the system (combined effect of the processor and query generator) were 70% and 87%. Training of the query component increased recall to 85% without changing precision.