基于BERT的手术名称标准化重排序算法

临床术语标准化是医学文本信息抽取中不可或缺的一项任务.临床上对于同一种诊断、手术、药品、检查、化验、症状等,往往会有多种不同的写法,术语标准化(归一)要解决的问题就是为临床上各种不同的说法找到对应的标准名称.在检索技术生成候选答案的基础上,该文提出了基于BERT(bidirectional encoder repres...

A BERT Based Reordering Method for Clinical Operation Term Normalization

Clinical term normalization is an indispensable task in clinical text information extraction. There are often various ways of writing about the same clinical term like diagnosis, operation, medicine, examination, laboratory test, symptom, etc., and term normalization is to find the corresponding standard name for different clinical terms. Based on the candidate answers generated by information retrieval tools, this paper proposes a method of reordering candidates based on BERT (Bidirectional Encoder Representation from Transformers). The experimental results show that the accuracy of single model and fusion model achieves 89.1% and 92.8%, respectively.