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Updated: May 3, 2026
Examining Online Syntactic Processing of Spoken Complex Sentences in Chinese Using Dual-Modal Interference Tasks
Published on: September 5, 2019
Extracting important information from Chinese Operation Notes with natural language processing methods
Hui Wang1, Weide Zhang2, Qiang Zeng3
1Shanghai Public Health Clinical Center, Institutes of Biomedical Sciences, and Key laboratory of Medical Molecular Virology, Ministry of Education and Health, Fudan University, Shanghai, China; Key Laboratory of Medical Imaging Computing and Computer Assisted Intervention of Shanghai, Fudan University, Shanghai, China; Key Laboratory of Systems Biology, Shanghai Institutes for Biological Sciences, Chinese Academy of Sciences, Shanghai, China.
Abstract:
Extracting information from unstructured clinical narratives is valuable for many clinical applications. Although natural Language Processing (NLP) methods have been profoundly studied in electronic medical records (EMR), few studies have explored NLP in extracting information from Chinese clinical narratives. In this study, we report the development and evaluation of extracting tumor-related information from operation notes of hepatic carcinomas which were written in Chinese. Using 86 operation notes manually annotated by physicians as the training set, we explored both rule-based and supervised machine-learning approaches. Evaluating on unseen 29 operation notes, our best approach yielded 69.6% in precision, 58.3% in recall and 63.5% F-score.