Abstract
Multi-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.
Original language | English (US) |
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Pages (from-to) | 371-377 |
Number of pages | 7 |
Journal | Journal of Ethnopharmacology |
Volume | 111 |
Issue number | 2 |
DOIs | |
State | Published - May 4 2007 |
Keywords
- Artificial intelligent method
- Herb pair
- Herbal medicine
- Herbal property
- Support vector machine
- Traditional Chinese medicine
ASJC Scopus subject areas
- Pharmacology
- Drug Discovery