期刊
出版社
MDPI
DOI: 10.3390/ijerph15030402
关键词
electronic medical records; temporal information; text structuring method; Chinese; information entropy
资金
- National Natural Science Foundation of China [71532002, 61702023]
- Humanities and Social Science Foundation of Ministry of Education of China [17YJC870015]
- Fundamental Fund for Humanities and Social Sciences of Beijing Jiaotong University [2016JBZD01]
- Fundamental Research Funds for the Central Universities [2016YJS057]
Chinese Electronic Medical Records (EMRs) contains a large number of complex medical free text which includes a variety of information, such as temporal information, patients' symptoms and laboratory data. However, as an important knowledge base, these unstructured text data in EMR are hard to process directly by computer to support further medical research. This paper proposes a novel text structuring method to extract knowledge from EMR texts and reorganize them in chronological order according to the temporal information in the text. By implementing some entropy-based algorithms as contrast, experiments evaluate the performance of the proposed method, which indicates the new method can significantly reduce the complexity of EMR text. This work is significant in structuring the EMR free text into temporal-structured data for further medical analysis.
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