基于数据挖掘的孟河名医杨博良治疗痢疾用药规律研究

Analysis on the principle of Yang Boliang for the treatment for dysentery based on apriori and clustering algorithm

目的：探讨杨博良先生治疗痢疾的用药经验。方法收集杨博良先生治疗痢疾的处方，在建立数据库的基础上，采用关联规则apriori算法、复杂系统熵聚类等无监督数据挖掘方法开展研究。结果治疗痢疾处方常用药物包括茯苓、法半夏、煨葛根等，核心药物组合包括“茯苓-黄芩-牡丹皮”“车前子-法半夏-六神曲”“木香炭-大黄炭-荷叶”等，新处方包括“车前子-法半夏-六神曲-生地炭-制香附”等。结论杨博良先生治疗痢疾经验丰富，多用清热燥湿和利水渗湿之品。

Objective To analyze the experience of Yang Boliang for the treatment of dysentery. Methods The prescriptions for dysentery that used by Yang Boliang were collected to build a database, and analyzed by the unsupervised data mining methods, such as apriori algorithm, entropy Clustering complex systems. Results Based on the analysis of 35 prescriptions, the most frequently used drug, the core drug combinations and the new prescriptions were mined from the database. The most frequently used drugs were tuckahoe, rhizoma pinellinae praeparata, and roasted radix puerariae. The core drug combinations were“tuckahoe- radix scutellariae-moutan bark”, “plantago seed-rhizoma pinellinae praeparata-maticated leaven”, and “charred radix aucklandiae-charred radix etrhizoma rhei-waterlily leaf”, etc. The new prescriptions were such as “plantago seed-rhizoma pinellinae praeparata-maticated leaven-charred radix rehmanniae recen-processed rhizoma Cyperi”. Conclusion Yang Boliang was well experienced in treating dysentery by using the drugs with clearing heat, and drying dampness, and clearing dampness by promoting diuresis.