Out-of-set association analysis of lung cancer drugs and symptoms based on clinical case data mining.

Background: There are 1.8 million lung cancer deaths worldwide, accounting for 18% of global cancer deaths, including 710,000 in China, accounting for 23.8% of all cancer deaths in China.

Analysis of the cluster efficacy and prescription characteristics of traditional Chinese medicine intervention for non-small cell lung cancer based on a clustering algorithm.

Background: In recent years, malignant tumors have gradually become one of the main causes of death for Chinese residents, of which lung cancer ranks first in both the incidence and mortality in China.

Objective: To mine the text of traditional Chinese medicine (TCM) clinical medical cases after data cleaning, analyze it, and study the experience of TCM doctors in treating non-small cell lung cancer (NSCLC).

Methods: The applied approach was based on the data mining methods of decentralized and hierarchical system clustering of data from a drug and prescription database.