Researsh of the medication rules of Chinese medicine for the treatment of epilepsy based on data mining

Objective: To explore the medication rules of traditional Chinese medicine (TCM) in the treatment of epilepsy through data mining utilizing the R language, thereby furnishing a foundation and insights for the herbal treatment of epilepsy. Methods: Clinical studies on the treatment of epilepsy with Chinese medicine were collected by searching China Knowledge Information Network (CNKI), Wanfang, VIP, and China Biomedical Literature Service System (SinoMed), and the data were screened and a database was established using Excel. Rstudio software was used to perform Chinese herbs frequency statistics, correlation analysis, association rule analysis and cluster analysis to explore the pattern of TCM medication. Results: According to the inclusion and exclusion criteria, 197 prescriptions were obtained, involving 325 kinds of Chinese herbs, with a frequency of 2453 times, in which the top three herbs in terms of frequency of use were Acorus calamus, Glycyrrhizae Radix Et Rhizoma, and Bombyx Batryticatus. The classification of the medicines' efficacy focused on liver-pacifying wind-extinguishing medicinal,tonifying medicinal,expectorant and antiasthmatic medicine,heat-clearing medicinal. The four qi of the medicines were predominantly cold and neutral, the five flavors were mainly sweet and pungent, and the attributed meridians were primarily the liver meridian, lung meridian, and spleen meridian. Correlation analysis revealed high correlation coefficients for drug pairs such as Os Draconis and Ostreae Concha. Association rule analysis yielded a total of 22 commonly used herbs combinations, while cluster analysis resulted in four herbs groupings. This study demonstrated that the identified medication rules can offer valuable insights for clinical TCM treatment of epilepsy, enhancing our understanding of the disease, clarifying treatment principles and medication rules, and providing a theoretical basis for clinical treatment and medication identification.