Abstract

The aim of the present study is to investigate the rules and characteristics of the clinical administration of traditional Chinese medicine (TCM) in the treatment of polycystic ovary syndrome (PCOS) using data mining methods. Medical cases of well-known contemporary TCM doctors treating PCOS were collected from the China National Knowledge Infrastructure, Chinese Biomedical Literature Service System, Wanfang, Chinese Scientific Journals Database, and PubMed; the data were then characterized, and a standardized database of medical cases was built. This database was used to (1) count the frequency of syndrome types and the herbs used in medical cases by data mining methods and (2) analyze drug association rules and systematic clustering methods. A total of 330 papers were included, involving 382 patients and a total of 1,427 consultations. The most common syndrome type was kidney deficiency; sputum stasis was the core pathological product and causative factor. A total of 364 herbs were used. Among them, 22 herbs were used >300 times, including Danggui (Angelicae Sinensis Radix), Tusizi (Semen Cuscutae), Fuling (Poria), Xiangfu (Nutgrass Galingale Rhizome), and Baizhu (Atractylodis Macrocephalae Rhizoma). Additionally, 22 binomial associations were obtained from the analysis of association rules; five clustering formulae were obtained via the analysis of high-frequency drug clusters; and 27 core combinations were obtained by k-means clustering of formula. In the treatment of PCOS, TCM is primarily employed as a combination approach involving tonifying the kidneys, strengthening the spleen, eliminating damp and dissolving phlegm, activating blood circulation, and resolving blood stasis. The core prescription is primarily a compound intervention based on the Cangfu Daotan pill, Liuwei Dihuang pill, and Taohong Siwu decoction.

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