电子病历中的临床术语描述形式具有多样性和不规范性,阻碍了医疗数据的分析和利用,因此对临床术语标准化的研究具有重要的现实意义。当前国内医疗机构临床术语标准化主要由人工完成,效率低,成本高。该文提出了一种基于BERT的临床术语标准化方法。该方法使用Jaccard相似度算法从标准术语集中挑选出候选词,基于BERT模型对原始词和候选词进行匹配得到标准化的结果。在CHIP2019临床术语标准化评测任务的数据集上准确率为90.04%。实验结果表明,该方法对于临床术语标准化任务是有效的。
Abstract
The diversity of clinical terms in electronic medical records hinder the analysis and utilization of medical data. To address this issue, this paper proposes a method of clinical term normalization based on BERT. The method uses Jaccard similarity to select the candidate words from the standard term set, and matches the original words and candidate words based on BERT model to obtain standardized results. Evaluated on the dataset of CHIP2019 clinical term normalization evaluation task, the method obtains 90.04% accuracy.
关键词
临床术语 /
标准化 /
BERT
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Key words
clinical term /
normalization /
BERT
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参考文献
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脚注
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基金
国家十三五重点研发计划(2016YFC0901902)
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