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X Demographics
Mendeley readers
Attention Score in Context
| Title |
Using association rules mining to explore pattern of Chinese medicinal formulae (prescription) in treating and preventing breast cancer recurrence and metastasis
|
|---|---|
| Published in |
Journal of Translational Medicine, September 2012
|
| DOI | 10.1186/1479-5876-10-s1-s12 |
| Pubmed ID | |
| Authors |
Yanhua He, Xiao Zheng, Cindy Sit, Wings TY Loo, ZhiYu Wang, Ting Xie, Bo Jia, Qiaobo Ye, Kamchuen Tsui, Louis WC Chow, Jianping Chen |
| Abstract |
Chinese herbal medicine is increasingly widely used as a complementary approach for control of breast cancer recurrence and metastasis. In this paper, we examined the implicit prescription patterns behind the Chinese medicinal formulae, so as to explore the Chinese medicinal compatibility patterns or rules in the treatment or control of breast cancer recurrence and metastasis. |
X Demographics
The data shown below were collected from the profile of 1 X user who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Italy | 1 | 100% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 1 | 100% |
Mendeley readers
The data shown below were compiled from readership statistics for 36 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Australia | 1 | 3% |
| Unknown | 35 | 97% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 6 | 17% |
| Student > Master | 6 | 17% |
| Student > Bachelor | 5 | 14% |
| Other | 3 | 8% |
| Researcher | 3 | 8% |
| Other | 9 | 25% |
| Unknown | 4 | 11% |
| Readers by discipline | Count | As % |
|---|---|---|
| Medicine and Dentistry | 11 | 31% |
| Computer Science | 5 | 14% |
| Nursing and Health Professions | 4 | 11% |
| Biochemistry, Genetics and Molecular Biology | 3 | 8% |
| Pharmacology, Toxicology and Pharmaceutical Science | 1 | 3% |
| Other | 7 | 19% |
| Unknown | 5 | 14% |
Attention Score in Context
This research output has an Altmetric Attention Score of 1. 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 23 November 2012.
All research outputs
#15,256,901
of 22,687,320 outputs
Outputs from Journal of Translational Medicine
#2,223
of 3,963 outputs
Outputs of similar age
#107,184
of 170,581 outputs
Outputs of similar age from Journal of Translational Medicine
#30
of 55 outputs
Altmetric has tracked 22,687,320 research outputs across all sources so far. This one is in the 22nd percentile – i.e., 22% of other outputs scored the same or lower than it.
So far Altmetric has tracked 3,963 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 10.5. This one is in the 31st percentile – i.e., 31% of its peers scored the same or lower than it.
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 170,581 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 27th percentile – i.e., 27% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 55 others from the same source and published within six weeks on either side of this one. This one is in the 34th percentile – i.e., 34% of its contemporaries scored the same or lower than it.