↓ Skip to main content

Exploring the combination and modular characteristics of herbs for alopecia treatment in traditional Chinese medicine: an association rule mining and network analysis study

Overview of attention for article published in BMC Complementary Medicine and Therapies, July 2018
Altmetric Badge

About this Attention Score

  • Average Attention Score compared to outputs of the same age
  • Good Attention Score compared to outputs of the same age and source (68th percentile)

Mentioned by

twitter
4 X users
video
1 YouTube creator

Citations

dimensions_citation
24 Dimensions

Readers on

mendeley
48 Mendeley
Title
Exploring the combination and modular characteristics of herbs for alopecia treatment in traditional Chinese medicine: an association rule mining and network analysis study
Published in
BMC Complementary Medicine and Therapies, July 2018
DOI 10.1186/s12906-018-2269-7
Pubmed ID
Authors

Jungtae Leem, Wonmo Jung, Yohwan Kim, Bonghyun Kim, Kyuseok Kim

Abstract

Although alopecia affects the quality of life, its pathogenesis is unknown, because cellular interactions in the hair follicle are complex. Several authors have suggested using herbal medicine to treat alopecia, and bioinformatics and network pharmacology may constitute a new research strategy in this regard because herbal medicines contain various chemical components. This study used association rule mining (ARM) and network analysis to analyze the combinations of medicinal herbs used to treat alopecia. We searched Chinese, Korean, and English databases for literature about alopecia treatment, extracting the names of each herbal prescription and herb. The meridian tropism and classification category of each herb were also investigated. Using ARM, we identified frequently combined two-herb and three-herb sets. Using network analysis, we divided the herbs into several modules according to prescription pattern. Fifty-six articles and 489 herbal medicines were included-312 internal and 177 external medicines. Among the 312 medicinal herbs used in internal medicine group, the most frequently combined two-herb set was Polygonum multiflorum Thunb. () and Angelica sinensis (Oliv.) Dlels (). The most frequently used three-herb combination was Polygonum multiflorum Thunb., Angelica sinensis (Oliv.) Dlels, and Ligusticum chuanxiong Hort. (). In network analysis, three modules were identified. The herbs of Module 1 were related to the liver and kidney meridians, and those of Module 3 were related to the Stomach meridian. We identified the frequency, characteristics, and functional modules of herb combinations frequently used in alopecia treatment. We confirmed the value of classical medicinal herb theory. This finding will prompt further bioinformatics and network pharmacology research on alopecia.

X Demographics

X Demographics

The data shown below were collected from the profiles of 4 X users who shared this research output. Click here to find out more about how the information was compiled.
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 48 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 48 100%

Demographic breakdown

Readers by professional status Count As %
Researcher 8 17%
Student > Postgraduate 5 10%
Student > Master 4 8%
Student > Bachelor 3 6%
Student > Ph. D. Student 2 4%
Other 7 15%
Unknown 19 40%
Readers by discipline Count As %
Medicine and Dentistry 6 13%
Pharmacology, Toxicology and Pharmaceutical Science 4 8%
Biochemistry, Genetics and Molecular Biology 3 6%
Agricultural and Biological Sciences 3 6%
Nursing and Health Professions 2 4%
Other 8 17%
Unknown 22 46%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 2. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 22 June 2023.
All research outputs
#15,138,336
of 24,476,221 outputs
Outputs from BMC Complementary Medicine and Therapies
#1,689
of 3,841 outputs
Outputs of similar age
#184,435
of 332,535 outputs
Outputs of similar age from BMC Complementary Medicine and Therapies
#24
of 73 outputs
Altmetric has tracked 24,476,221 research outputs across all sources so far. This one is in the 37th percentile – i.e., 37% of other outputs scored the same or lower than it.
So far Altmetric has tracked 3,841 research outputs from this source. They typically receive more attention than average, with a mean Attention Score of 9.1. This one has gotten more attention than average, scoring higher than 54% of its peers.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 332,535 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 42nd percentile – i.e., 42% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 73 others from the same source and published within six weeks on either side of this one. This one has gotten more attention than average, scoring higher than 68% of its contemporaries.