Improved FP-Growth Algorithm Based on Spark Platform and its Analysis and Excavation in Clinical Data of Lung Cancer

OBJECTIVE: To mine the core prescription of traditional Chinese medicine for lung cancer medical record. METHODS: Deep FP-Growth algorithm, an improved FP-Growth algorithm, was implemented under the Spark environment and was used to excavate the frequent patterns and association rules of traditional Chinese medicine in the treatment of lung cancer cases. RESULTS: The core prescription of several diseases with higher frequency of occurrence was excavated. CONCLUSION: Deep FP-Growth algorithm based on Spark platform can effectively excavate the core prescription of traditional Chinese medicine in the treatment of lung cancer.