Analysis on the principle of Yang Boliang for the treatment for dysentery based on apriori and clustering algorithm / 国际中医中药杂志

ABSTRACT

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.