方剂可以概括为中医辨证论治体系的数据集合,文本挖掘技术可将隐含在数据中的配伍规律以可理解方式进行表述。本研究选择中国生物医学文献数据库为载体,类风湿性关节炎(RA)、强直性脊柱炎(AS)、溃疡性结肠炎(UC)和哮喘(Asthma)4种自身免疫性疾病为研究对象,采用数学和统计的方法,获取高频率、协同出现的关键药对,探寻中医治疗这4种疾病的用药规律。结果表明,采用这种计算方法总结出的4种疾病常用中药规律与其病机是相符的,且黄芪作为这4种疾病共同使用的常用中药,可能作用于自身免疫性疾病的特异性病理靶标。
Prescription can be acted as data set of zheng differentiation-treatment system. The implied regularity of this data set can be presented with text mining technique. In this research, we select Chinese BioMedical Literature Database as vector to analyze the Chinese herb medication regularity of Rheumatoid Arthritis, Ankylosing Spondyli- tis, Ulcerative Colitis and Asthma. The high frequency and synergism herbs pattern are obtained. The results show that the medication regularity get with this computational method are in accordance with the pathogenesis of these four diseases. Besides, Huang Qi (Radix Astragali) is included in these four diseases, which could affect the specific pathological target of autoimmunity disease.