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A Multilayer Network Constructed for Herb and Prescription Efficacy Analysis

Xindi Huang1, Liwei Liang1, Sakirin Tam2, Hao Liang3, Xiong Cai4, Changsong Ding1,5,*

1 School of Informatics, Hunan University of Chinese Medicine, Changsha, 410208, China
2 Faculty of Science and Information Technology, Phnom Penh International University, Phnom Penh, 12253, Cambodia
3 Institute of TCM Diagnostics, Hunan University of Chinese Medicine, Changsha, 410208, China
4 Institute of Innovation and Applied Research in Chinese Medicine, Hunan University of Chinese Medicine, Changsha, 410208, China
5 Big Data Analysis Laboratory of Traditional Chinese Medicine, Hunan University of Chinese Medicine, Changsha, 410208, China

* Corresponding Author: Changsong Ding. Email: email

Computer Systems Science and Engineering 2024, 48(3), 691-704. https://doi.org/10.32604/csse.2022.029970

Abstract

Chinese Medicine (CM) has been widely used as an important avenue for disease prevention and treatment in China especially in the form of CM prescriptions combining sets of herbs to address patients’ symptoms and syndromes. However, the selection and compatibility of herbs are complex and abstract due to intrinsic relationships between herbal properties and their overall functions. Network analysis is applied to demonstrate the complex relationships between individual herbal efficacy and the overall function of CM prescriptions. To illustrate their connections and correlations, prescription function (PF), prescription herb (PH), and herbal efficacy (HE) intra-networks are proposed based on CM theory to identify relationships between herbs and prescriptions. These three networks are then connected by PF-PH and PH-HE interlayer networks adopting herb dosage to form a multidimensional heterogeneous network, a Prescription-Herb-Function Network (PHFN). The network is applied to 112 classic prescriptions from Treatise on Exogenous Febrile and Miscellaneous Diseases to illustrate the application of PHFN. The PHFN is constructed including 146 functions in PF intra network, 89 herbs in the PH intra network, and 163 herbal efficacies in the HE intra network. The results show that herb pairs with synergistic actions have stronger relevance, such as licorice-cassia twig, licorice-Chinese date, fresh ginger-Chinese date, etc. The integration of dosage to the network helps to indicate the main herbs for cluster analysis and automatic formulation. PHFN also reveals the internal relationships between the functions of prescriptions and composed herbal efficacies.

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Cite This Article

APA Style
Huang, X., Liang, L., Tam, S., Liang, H., Cai, X. et al. (2024). A multilayer network constructed for herb and prescription efficacy analysis. Computer Systems Science and Engineering, 48(3), 691-704. https://doi.org/10.32604/csse.2022.029970
Vancouver Style
Huang X, Liang L, Tam S, Liang H, Cai X, Ding C. A multilayer network constructed for herb and prescription efficacy analysis. Comput Syst Sci Eng. 2024;48(3):691-704 https://doi.org/10.32604/csse.2022.029970
IEEE Style
X. Huang, L. Liang, S. Tam, H. Liang, X. Cai, and C. Ding "A Multilayer Network Constructed for Herb and Prescription Efficacy Analysis," Comput. Syst. Sci. Eng., vol. 48, no. 3, pp. 691-704. 2024. https://doi.org/10.32604/csse.2022.029970



cc This work is licensed under a Creative Commons Attribution 4.0 International License , which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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