Automatic Deidentification by using Sentence Features and Label Consistency
Automatic Deidentification by using Sentence Features and Label Consistency
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发表时间：
2006
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通讯作者：
E. Aramaki;Takeshi Imai;K. Miyo;K. Ohe
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作者：
E. Aramaki;Takeshi Imai;K. Miyo;K. Ohe
临床病历的非识别性问题已经引起了医学界的广泛关注。由于临床记录中的文本大多是不符合语法和支离破碎的，以前的方法只依赖于本地信息，即围绕当前目标词的上下文单词。本文提出了一种新的方法，采用三种类型的非局部特征，这不是来自周围的话：（1）句子特征，对应于前/下一个句子的信息和（2）标签一致性，倾向于相同的标签相同的单词序列。实验结果表明，高性能（准确率98.29%，召回率96.66%，F-措施97.47），证明了所提出的方法的可行性。
Deidentification of clinical records has drawn a great deal of attention in the medical field. Since texts in clinical records are mostly ungrammatical and fragmented, previous approaches have relied only on local information, namely contextual words surrounding a current target word. The present paper proposes a new approach employing three types of non-local features, which does not come from surrounding words: (1) sentence features, corresponding to the previous/next sentence information and (2) label consistency, preferring the same label for the same word sequence. The experimental results showed high performance (precision 98.29%; recall 96.66%; f-measure 97.47), demonstrating the feasibility of the proposed approach.