ArticleAMIA ... Annual Symposium proceedings. AMIA Symposium2016
CMedTEX: A Rule-based Temporal Expression Extraction and Normalization System for Chinese Clinical Notes.
Article in AMIA ... Annual Symposium proceedings. AMIA Symposium, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
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Who cites it
3 citing papers in PubMed.
- Temporal Annotation of German Clinical Language in Real and Synthetic Clinical Documents: Corpus Development and Baseline Tagger Validation Study.Journal of medical Internet research · 2026Article
- Temporal Expression Classification and Normalization From Chinese Narrative Clinical Texts: Pattern Learning Approach.JMIR medical informatics · 2020Article
- Constructing fine-grained entity recognition corpora based on clinical records of traditional Chinese medicine.BMC medical informatics and decision making · 2020Article
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Authors and funding
9 authors.
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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.
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28269878PMC5333232What OpenQuestion holds
Registered trials
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