Acupoint Selection Rule Mining of Premature Ovarian Failure Treatment with Acupuncture and Moxibustion Based on the Data Analysis of Clinical Literature

Han, Xiao; Fan, Yanni; Zhao, Haijun; Wang, Shijun; Shen, Tian; Zhang, Hongyuan; Liu, Danhong; Zhang, Ruqi; Zhang, Jing; We, Shi

doi:10.1109/bibm.2018.8621095

Cited by 2 publications

(1 citation statement)

References 21 publications

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“…Meanwhile, the area that each acupoint can activate and regulate is also different. Therefore, researchers pay more attention to the synergistic effect of acupoint combination [ 21 ] and try to find the optimal acupuncture prescription for specific diseases based on this effect [ 22 , 23 ]. For example, the authors in [ 24 ] used artificial neural network (ANN) to train the relationship between symptom information and selected acupoints, selected 11 key nodes with the highest average precision score, and systematically described acupoint indications through data mining technology.…”

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confidence: 99%

A Key Node Mining Method Based on Acupoint‐Disease Network (ADN): A New Perspective for Exploring Acupoint Specificity

Shi

Liu

Cui

et al. 2020

Evidence-Based Complementary and Alternative Medicine

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In the process of treating pro-diseases with acupuncture, traditional Chinese medicine (TCM) doctors may fine-tune acupuncture prescriptions according to different prior experiences. Different prescriptions will affect the efficiency and effect of acupuncture treatment, and even excessive acupoint selection may cause psychological pressure on patients. We still lack an effective means to analyze the meridian system and acupoint specificity to clarify the mapping relationship between acupoints and diseases. Given the inability of modern medical technology to provide effective evidence support for meridians and acupoints, we combined acupuncture theory with network science for an interdisciplinary discussion. In this paper, we constructed a weighted undirected acupoint-disease network (ADN) based on clinical acupuncture prescription literature and proposed a high-specificity key node mining method based on ADN. Combined with the principle of acupoint selection in TCM, the proposed method balanced the contribution of local areas to the network based on the distribution characteristics of meridians and selected 30 key acupoints with high influence on the global topology according to the evaluation index of key nodes. Finally, we compared the proposed method with the other six classical node importance evaluation algorithms in terms of resolution, network loss, and accuracy. The comprehensive results show that the marked key acupoint nodes make outstanding contributions to the connectivity, topological structure, and weighted benefits of the network, and the stability and specificity of the algorithm guarantee the reliability of the key acupoint nodes. We consider that these key acupoints with high centrality in ADN can be used as core acupoints to help researchers explore targeted and high-impact acupoint combinations under resource constraints and optimize existing acupuncture prescriptions.

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