| Literature DB >> 28269878 |
Zengjian Liu1, Buzhou Tang1, Xiaolong Wang1, Qingcai Chen1, Haodi Li1, Junzhao Bu1, Jingzhi Jiang1, Qiwen Deng2, Suisong Zhu2.
Abstract
Time is an important aspect of information and is very useful for information utilization. The goal of this study was to analyze the challenges of temporal expression (TE) extraction and normalization in Chinese clinical notes by assessing the performance of a rule-based system developed by us on a manually annotated corpus (including 1,778 clinical notes of 281 hospitalized patients). In order to develop system conveniently, we divided TEs into three categories: direct, indirect and uncertain TEs, and designed different rules for each category of them. Evaluation on the independent test set shows that our system achieves an F-score of93.40% on TE extraction, and an accuracy of 92.58% on TE normalization under "exact-match" criterion. Compared with HeidelTime for Chinese newswire text, our system is much better, indicating that it is necessary to develop a specific TE extraction and normalization system for Chinese clinical notes because of domain difference.Entities:
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Year: 2017 PMID： 28269878 PMCID： PMC5333232
Source DB: PubMed Journal: AMIA Annu Symp Proc ISSN： 1559-4076