Reasonable Evaluation Model of Pediatric Disease Based on pharmacology and Data Mining
With the growing medical technology and many major achievements, the research on the laws of common diseases in pediatrics is also developing rapidly. The resulting drug data has increased exponentially, forming a large number of common disease medication data. So much data contains a lot of information with important scientific value. Therefore, the discovery of the pathogenic sites of pediatric diseases has positive significance for the prevention and treatment of human life and health. The main purpose of the research is to establish a reasonable evaluation model based on pediatric disease pharmacology and computer science, analyze the data of common medications, and find out the sites that are significantly associated with diseases in the data of common disease medications. In this paper, we use a complex network, R language, rank sum test, displacement test and other data mining methods to retrospectively study some common pediatric cases (such as pediatric cough cases), summarize their medication rules for treating cough in children, and study cough disease. The relationship between the network of the newly diagnosed symptoms and the curative effect provides a reference for the clinical use of traditional Chinese medicine in the treatment of common pediatric diseases, providing ideas for more accurate and effective diagnosis and treatment.