Identification of candidate medicinal herbs for skincare via data mining of the classic Donguibogam text on Korean medicine
Background: Korean cosmetics are widely exported throughout Asia. Cosmetics exploiting traditional Korean medicine lead this trend; thus, the traditional medicinal literature has been invaluable in terms of cosmetic development. We sought candidate medicinal herbs for skincare. Methods: We used data...
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| Main Authors: | , , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Elsevier
2020-12-01
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| Series: | Integrative Medicine Research |
| Subjects: | |
| Online Access: | http://www.sciencedirect.com/science/article/pii/S2213422020300688 |
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| Summary: | Background: Korean cosmetics are widely exported throughout Asia. Cosmetics exploiting traditional Korean medicine lead this trend; thus, the traditional medicinal literature has been invaluable in terms of cosmetic development. We sought candidate medicinal herbs for skincare. Methods: We used data mining to investigate associations between medicinal herbs and skin-related keywords (SRKs) in a classical text. We selected 26 SRKs used in the Donguibogam text; these referred to 626 medicinal herbs. Using a term frequency-inverse document frequency approach, we extracted data on herbal characteristics by assessing the co-occurrence frequencies of 52 medicinal herbs and the 26 SRKs. Results: We extracted the characteristics of the 52 herbs, each of which exhibited a distinct skin-related action profile. For example Ginseng Radix was associated at a high-level with tonification and anti-aging, but Rehmanniae Radix exhibited a stronger association with anti-aging. Of the 52 herbs, 46 had been subjected to at least one modern study on skincare-related efficacy. Conclusions: We made a comprehensive list of candidate medicinal herbs for skincare via data mining a classical medical text. This enhances our understanding of such herbs and will help with discovering new candidate herbs. |
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| ISSN: | 2213-4220 |