THCluster: herb supplements categorization for precision traditional Chinese medicine
There has been a continuing demand for traditional and complementary medicine worldwide. A fundamental and important topic in Traditional Chinese Medicine (TCM) is to optimize the prescription and to detect herb regularities from TCM data. In this paper, we propose a novel clustering model to solve...
| Main Authors: | , , , , , , , |
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| Format: | Conference or Workshop Item |
| Published: |
2017
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| Subjects: | |
| Online Access: | https://eprints.nottingham.ac.uk/48067/ |
| _version_ | 1848797683388514304 |
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| author | Ruan, Chunyang Wang, Ye Zhang, Yanchun Ma, Jiangang Chen, Huijuan Aickelin, Uwe Zhu, Shanfeng Zhang, Ting |
| author_facet | Ruan, Chunyang Wang, Ye Zhang, Yanchun Ma, Jiangang Chen, Huijuan Aickelin, Uwe Zhu, Shanfeng Zhang, Ting |
| author_sort | Ruan, Chunyang |
| building | Nottingham Research Data Repository |
| collection | Online Access |
| description | There has been a continuing demand for traditional and complementary medicine worldwide. A fundamental and important topic in Traditional Chinese Medicine (TCM) is to optimize the prescription and to detect herb regularities from TCM data. In this paper, we propose a novel clustering model to solve this general problem of herb categorization, a pivotal task of prescription optimization and herb regularities. The model utilizes Random Walks method, Bayesian rules and Expectation Maximization (EM) models to complete a clustering analysis effectively on a heterogeneous information network. We performed extensive experiments on the real-world datasets and compared our method with other algorithms and experts. Experimental results have demonstrated the effectiveness of the proposed model for discovering useful categorization of herbs and its potential clinical manifestations. |
| first_indexed | 2025-11-14T20:07:46Z |
| format | Conference or Workshop Item |
| id | nottingham-48067 |
| institution | University of Nottingham Malaysia Campus |
| institution_category | Local University |
| last_indexed | 2025-11-14T20:07:46Z |
| publishDate | 2017 |
| recordtype | eprints |
| repository_type | Digital Repository |
| spelling | nottingham-480672020-05-04T19:17:37Z https://eprints.nottingham.ac.uk/48067/ THCluster: herb supplements categorization for precision traditional Chinese medicine Ruan, Chunyang Wang, Ye Zhang, Yanchun Ma, Jiangang Chen, Huijuan Aickelin, Uwe Zhu, Shanfeng Zhang, Ting There has been a continuing demand for traditional and complementary medicine worldwide. A fundamental and important topic in Traditional Chinese Medicine (TCM) is to optimize the prescription and to detect herb regularities from TCM data. In this paper, we propose a novel clustering model to solve this general problem of herb categorization, a pivotal task of prescription optimization and herb regularities. The model utilizes Random Walks method, Bayesian rules and Expectation Maximization (EM) models to complete a clustering analysis effectively on a heterogeneous information network. We performed extensive experiments on the real-world datasets and compared our method with other algorithms and experts. Experimental results have demonstrated the effectiveness of the proposed model for discovering useful categorization of herbs and its potential clinical manifestations. 2017-11-13 Conference or Workshop Item PeerReviewed Ruan, Chunyang, Wang, Ye, Zhang, Yanchun, Ma, Jiangang, Chen, Huijuan, Aickelin, Uwe, Zhu, Shanfeng and Zhang, Ting (2017) THCluster: herb supplements categorization for precision traditional Chinese medicine. In: IEEE International Conference on Bioinformatics and Biomedicine (IEEE BIBM 2017), 13-16 Nov 2017, Kansas City, Mo., USA. Herb categorization Heterogeneous information network Clustering http://ieeexplore.ieee.org/abstract/document/8217685/ |
| spellingShingle | Herb categorization Heterogeneous information network Clustering Ruan, Chunyang Wang, Ye Zhang, Yanchun Ma, Jiangang Chen, Huijuan Aickelin, Uwe Zhu, Shanfeng Zhang, Ting THCluster: herb supplements categorization for precision traditional Chinese medicine |
| title | THCluster: herb supplements categorization for precision traditional Chinese medicine |
| title_full | THCluster: herb supplements categorization for precision traditional Chinese medicine |
| title_fullStr | THCluster: herb supplements categorization for precision traditional Chinese medicine |
| title_full_unstemmed | THCluster: herb supplements categorization for precision traditional Chinese medicine |
| title_short | THCluster: herb supplements categorization for precision traditional Chinese medicine |
| title_sort | thcluster: herb supplements categorization for precision traditional chinese medicine |
| topic | Herb categorization Heterogeneous information network Clustering |
| url | https://eprints.nottingham.ac.uk/48067/ https://eprints.nottingham.ac.uk/48067/ |