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. OBJECTIVE: To explore the out-of-set association rules of lung cancer symptoms and drugs through text mining of traditional Chinese medicine (TCM) treatment of lung cancer, and form medical case analysis to analyze the experience of TCM syndrome differentiation in its treatment. METHODS: The medical records of all patients diagnosed with lung cancer in Nanjing Chest Hospital from January to December 2018 were collected, and the out-of-set association analysis was performed using the MedCase v5.2 TCM clinical scientific research auxiliary platform based on the frequent pattern growth enhanced association analysis algorithm. RESULTS: In terms of TCM treatment of lung cancer, the clinical symptoms with high correlation included cough, expectoration, chest distress, and white phlegm; and the drugs with high correlation included Pinellia ternata, licorice root, white Atractylodes rhizome, and Radix Ophiopogonis; with the prescriptions based on Erchen and Maimendong decoctions. CONCLUSION: This analytical study of the medical cases of TCM treatment for lung cancer was performed using data mining techniques, and the out-of-set association rules between clinical symptoms and drugs were analyzed, including the understanding of lung cancer in TCM. Moreover, the essence of experience in drug use was gathered, providing significant scientific guidance for the clinical treatment of lung cancer.

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. This study involved 215 patients, 287 cases, and 147 types of clinical drugs. RESULTS: The data analysis of the clinical treatment of NSCLC in TCM showed that Erchen Decoction was the main method for the treatment of non-small cell lung cancer in clinical treatment of non-small cell lung cancer. Junjian recipes were close to each other, with Banzhilian, Lobelia, Shanci Mushroom, Hedyotis diffusa to anticancer and detoxify. CONCLUSION: This study analyzed the core TCM prescription for NSCLC by collecting the empirical essence and characteristics of specific medications. It has some guiding scientific significance for the clinical treatment of lung cancer.