基于证候要素定向文本挖掘类风湿性关节炎中药配伍规律

摘要

Objective: Based on the keywords of patterns in traditional Chinese medicine on rheumatoid arthritis, we applied the syndrome element directed mining algorithm and got the rules of Chinese herbal medicines according to these patterns. Method; The original data set on term "rheumatoid arthritis" was downloaded from SinoMed. Then, the data set was formatted. Based on the keywords of cold, heat, deficiency, and stasis, together with noises taken away manually, we mined the rules of Chinese herbal medicines. Results: Rules of Chinese herbal medicines have significant differences between hot and cold pattern, patterns of deficiency and stasis are similar, another interesting fact is that decoction of guizhi-shaoyao-zhimu is associated with all the syndromes in our mining process. Conclusion; Our approach of pattern-directed text mining can get the rules of Chinese herbal medicines. What' s more, the mining results can be taken as references in clinical practices.%目的:以类风湿性关节炎证候要素为关键词,定向文本挖掘中药配伍规律.方法:在数据库中收集治疗类风湿性关节炎文献数据,格式化后,以“寒”、“热”、“虚”、“瘀”为挖掘词挖掘,结合人工降噪,分析配伍规律.结果:寒证、热证用药对比鲜明,虚证、瘀证用药相似,各证型均涉及桂枝芍药知母汤.结论:以证候定向文本挖掘方法,可总结中药配伍规律,为临床提供参考.