Research on Medication Rules of Famous TCM Physicians in Treating Lung Cancer Based on Hierarchical Community Partition Algorithm

Corresponding author: Yang Tao, taoyang1111@126.com

DOI: 10.12201/bmr.202110.00020

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  Abstract: Objective To explore medication rules of famous famous TCM physicians in the treatment of lung cancer. Methods 795 lung cancer prescriptions were used to construct the weighted network of Chinese medicine. The hierarchical community partition algorithm was used to partition the network. The classification was determined according to the order of drug merger and the modularity of the community, and the hierarchical information was extracted and visulized from the network. Results The algorithm detected two-layer Chinese medicine communities. Three TCM communities (C1, C2, C3) in the first laye, and five (C1.1, C1.2, C3.1, C3.2, C3.3) in the second layer. Analyzing the effect of herbs in each community, we find that communities mainly dissolve phlegm and remove blood stasis, and some communities have the effect of clearing heat and detoxification, nourishing yin and moistening dryness, promoting qi and relieving pain, warming the spleen and so on. It can be inferred from the result that the pathogenesis of lung cancer is very complex, mainly due to the combination of phlegm and blood stasis, and also has correlation with phlegm-heat, qi-deficiency, yin-deficiency, qi-stagnation, middle-jiao cold and so on. Clinical treatment should be flexible use of Chinese medicine based on syndrome differentiation. Conclusion With the help of hierarchical community division algorithm, we can mine the medication rules of famous Chinese medicine in the treatment of lung cancer effectively, which is of great significance to the digital inheritance of diagnosis and treatment experience of famous TCM physicians.

  Key words: hierarchical community division; lung cancer; medication rule; TCM diagnosis and treatment experience

  Submit time: 8 November 2021

  Copyright: The copyright holder for this preprint is the author/funder, who has granted biomedRxiv a license to display the preprint in perpetuity.
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