基于树模型的医学检查文本报告结构化处理方法

Duan Yifan, Pan Qiao, Golddy Indra Kumara, Dehua Chen
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引用次数: 2

摘要

医院提供了大量的医学文本报告。这些报告由医生撰写或由医疗设备生成,详细说明患者的临床问题和诊断。这些报告包含非常有价值的信息,可用于未来的患者诊断。但是这些医疗报告存在的问题是大多数报告都不是结构化的,所以我们将无法充分利用这些信息。本文提出了一种基于树模型的结构化处理方法。首先,对文本报表进行数据处理,使数据更加准确。然后建立词性词典,从文本报告中的所有单词中获取词性。每个句子之间的语义关系需要通过依赖句法分析得到。通过结合词性和语义关系,提出了一种规则来建立树形模型。实验结果表明,该方法能较好地实现甲状腺超声中文报告的结构化。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Structured Processing Method of Medical Examination Text Reports Based on Tree Model
There are a lot of medical text reports available provided by hospital. These reports are written by doctors or generated by medical equipment specifying the clinical problems and diagnosis of patients. These reports contain very valuable information that can be useful for future patient diagnosis. But the problem occurred with these medical reports are most of them are not structured, so we will not be able to leverage full advantage of the information. This paper proposes a structured processing method based on tree model. First, data processing is performed on the text reports in order to make the data more accurate. Then establish part of speech dictionary to obtain part of speech from all words in the text reports. Semantic relationships between each sentence need to be obtained by performing dependency syntax analysis. By combining part of speech and semantic relationship we propose a rules to establish a tree model. The experiment has shown that this method can be used to achieve a good result for structuring thyroid ultrasound reports in Chinese language.
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