Analysis of medication data of women with uterine fibroids based on data mining technology

Abstract

The purpose of this study was to analyze the characteristics of the diagnosis and treatment of female uterine fibroids based on data mining technology and the medication rule. Clinical literature related to the treatment of uterine fibroids by Chinese National Knowledge Infrastructure (CNKI) from 2004 to 2018 were searched, and the literature meeting the requirements were selected according to the inclusion criteria and exclusion criteria. The contents of the prescription were recorded into the database, and the results of drug frequency, common drugs and core rules, etc. were obtained by the rule analysis of the software, so as to analyze the medication rules of modern doctors in treating uterine fibroids. Through research and analysis, it showed that common clinical drugs include leuprorelin (GnRH-a), danazol (androgen), gestrinone (progestin), mifepristone (progesterone receptor antagonist), and some cases of combination therapy. Based on the analysis of the frequency of drug, treatment effect and adverse drug reactions, it was found that the clinical application of mifepristone in the treatment of uterine fibroids was relatively common, with significant drug effect and mild adverse reactions, which was worthy of clinical promotion and application. Therefore, the results of this study provide a new basis for the clinical and basic research of traditional Chinese medicine in the treatment of uterine fibroids, but it still needs the verification of expert interpretation, experimental research and other methods.

Keywords

• Uterine fibroids
• Data mining
• Medical treatment
• Mifepristone
• Danazol