Application And Research Of Data Mining On Biomedical Knowledge Base

In the rapid development era, the development of science and technology changes with each passing day, biological and medical instruments become more and more precise, the hospital information system and biological experiments produce huge amounts of medical data and biological data. Based on three disciplines of informatics, biomedicine and data mining, we developed a biomedical knowledge base, based on this knowledge base, we can explore the molecular mechanism of traditional chinese medicine and mine the association rules among syndrome, symptom, treatment, prescription of disease, which provides data support for the clinical application of traditional chinese medicine and drug studies and also provides a new idea for in-depth and scientific clinical diagnosis research.The paper takes biomedicine as application background and develops a biomedical knowledge base through integrating databases which in different types, different formats and different research area using data collection and data preprocessing. The knowledge base provides comprehensive and complete information for researches finding new biomedical rules and knowledge. In this paper, we bring forward a new FP-Growth algorithm by introducing theory and contrasting merits and faults of Apriori and FP-Growth algorithm. Comparison is made with the performance of original and new FP-Growth by experiment. The experiment shows that both of two algorithms have merits and faults, but when the database increased to a certain extent or minimum support decreased to a certain extent, the efficiency of new FP-Growth is higher than original FP-Growth. At last, based on the association rule thought, mining the associate rules among syndrome, symptom, treatment, and prescription of rheumatoid arthritis in biomedical knowledge base by using new FP-Growth algorithm, this idea conducts more effective research on TCM clinical medication regularity and compatibility of drugs, and also verifies the importance of constructing biomedical knowledge base.