Please use this identifier to cite or link to this item: https://doi.org/10.1016/j.jep.2006.11.037
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dc.titleAre herb-pairs of traditional Chinese medicine distinguishable from others? Pattern analysis and artificial intelligence classification study of traditionally defined herbal properties
dc.contributor.authorUng, C.Y.
dc.contributor.authorLi, H.
dc.contributor.authorCao, Z.W.
dc.contributor.authorLi, Y.X.
dc.contributor.authorChen, Y.Z.
dc.date.accessioned2014-10-29T01:48:58Z
dc.date.available2014-10-29T01:48:58Z
dc.date.issued2007-05-04
dc.identifier.citationUng, C.Y., Li, H., Cao, Z.W., Li, Y.X., Chen, Y.Z. (2007-05-04). Are herb-pairs of traditional Chinese medicine distinguishable from others? Pattern analysis and artificial intelligence classification study of traditionally defined herbal properties. Journal of Ethnopharmacology 111 (2) : 371-377. ScholarBank@NUS Repository. https://doi.org/10.1016/j.jep.2006.11.037
dc.identifier.issn03788741
dc.identifier.urihttp://scholarbank.nus.edu.sg/handle/10635/105678
dc.description.abstractMulti-herb prescriptions of traditional Chinese medicine (TCM) often include special herb-pairs for mutual enhancement, assistance, and restraint. These TCM herb-pairs have been assembled and interpreted based on traditionally defined herbal properties (TCM-HPs) without knowledge of mechanism of their assumed synergy. While these mechanisms are yet to be determined, properties of TCM herb-pairs can be investigated to determine if they exhibit features consistent with their claimed unique synergistic combinations. We analyzed distribution patterns of TCM-HPs of TCM herb-pairs to detect signs indicative of possible synergy and used artificial intelligence (AI) methods to examine whether combination of their TCM-HPs are distinguishable from those of non-TCM herb-pairs assembled by random combinations and by modification of known TCM herb-pairs. Patterns of the majority of 394 known TCM herb-pairs were found to exhibit signs of herb-pair correlation. Three AI systems, trained and tested by using 394 TCM herb-pairs and 2470 non-TCM herb-pairs, correctly classified 72.1-87.9% of TCM herb-pairs and 91.6-97.6% of the non-TCM herb-pairs. The best AI system predicted 96.3% of the 27 known non-TCM herb-pairs and 99.7% of the other 1,065,100 possible herb-pairs as non-TCM herb-pairs. Our studies suggest that TCM-HPs of known TCM herb-pairs contain features distinguishable from those of non-TCM herb-pairs consistent with their claimed synergistic or modulating combinations. © 2006 Elsevier Ireland Ltd. All rights reserved.
dc.description.urihttp://libproxy1.nus.edu.sg/login?url=http://dx.doi.org/10.1016/j.jep.2006.11.037
dc.sourceScopus
dc.subjectArtificial intelligent method
dc.subjectHerb pair
dc.subjectHerbal medicine
dc.subjectHerbal property
dc.subjectSupport vector machine
dc.subjectTraditional Chinese medicine
dc.typeArticle
dc.contributor.departmentPHARMACY
dc.description.doi10.1016/j.jep.2006.11.037
dc.description.sourcetitleJournal of Ethnopharmacology
dc.description.volume111
dc.description.issue2
dc.description.page371-377
dc.description.codenJOETD
dc.identifier.isiut000246166400023
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