中医药临床随机对照试验文献结构化信息的自动化提取及信息质量评价

doi:10.20047/j.issn1673-7210.2023.11.42

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Abstract Objective To improve the utilization rate of data information in the literature of randomized controlled trials of traditional Chinese medicine (RCTs), this subject automatically extracted structured information in the included literature and evaluated the extracted information. Methods From January 1986 to December 2020, the CNKI, Wanfang Data, and VIP were searched and sorted out the clinical RCT literatures, of six diseases including diabetes, rheumatoid arthritis, obesity, knee osteoarthritis, pediatric diarrhea and colorectal cancer. A total of 5 506 articles were randomly included. Optical character recognition technology was used to identify documents in portable document format, convert them into text format, and regular expressions were used to extract information from the documents. From the information extraction rate and accuracy of two aspects were evaluated. Results The study found that the extraction rates of “data”, “method”, “total number of participants”, “age of participants”, “number of participants”, “duration of treatment”, “exclusion criteria”, “inclusion criteria”, and “fund” were 96.60%, 93.30%, 92.60%, 42.23%, 28.29%, 80.20%, 62.60%, 46.00% and 21.10%, respectively, and the accuracy of nine fields were 97.9%, 98.9%, 89.7%, 100.0%, 100.0%, 94.5%, 97.3%, 89.0% and 94.7%, respectively. Conclusion Traditional Chinese medicine clinical RCT literatures can identify and judge the integrity of the structured information of literatures by automatic means, and the extracted structured information can provide data support for the construction of clinical RCTs trial network system of traditional Chinese medicine. On this basis, the author puts forward the idea of structured writing of traditional Chinese medicine clinical RCT literatures.

Key words： Traditional Chinese medicine Randomized controlled trial Optical character recognition Structured Scientific writing

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	ZHANG Yunan LIU Heyuan HUANG Zhe DOU Zhili HAN Dongran▲

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ZHANG Yunan LIU Heyuan HUANG Zhe DOU Zhili HAN Dongran▲. Automatic extraction and information quality evaluation of structured information in clinical randomized controlled trials of traditional Chinese medicine[J]. 中国医药导报, 2023, 20(11): 183-187,192.

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https://www.yiyaodaobao.com.cn/EN/10.20047/j.issn1673-7210.2023.11.42 OR https://www.yiyaodaobao.com.cn/EN/Y2023/V20/I11/183

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