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Attention Score in Context
| Title |
Computer-assisted lip diagnosis on traditional Chinese medicine using multi-class support vector machines
|
|---|---|
| Published in |
BMC Complementary Medicine and Therapies, August 2012
|
| DOI | 10.1186/1472-6882-12-127 |
| Pubmed ID | |
| Authors |
FuFeng Li, Changbo Zhao, Zheng Xia, Yiqin Wang, Xiaobo Zhou, Guo-Zheng Li |
| Abstract |
In Traditional Chinese Medicine (TCM), the lip diagnosis is an important diagnostic method which has a long history and is applied widely. The lip color of a person is considered as a symptom to reflect the physical conditions of organs in the body. However, the traditional diagnostic approach is mainly based on observation by doctor's nude eyes, which is non-quantitative and subjective. The non-quantitative approach largely depends on the doctor's experience and influences accurate the diagnosis and treatment in TCM. Developing new quantification methods to identify the exact syndrome based on the lip diagnosis of TCM becomes urgent and important. In this paper, we design a computer-assisted classification model to provide an automatic and quantitative approach for the diagnosis of TCM based on the lip images. |
X Demographics
The data shown below were collected from the profiles of 3 X users who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Taiwan | 1 | 33% |
| United Kingdom | 1 | 33% |
| Unknown | 1 | 33% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Scientists | 1 | 33% |
| Members of the public | 1 | 33% |
| Science communicators (journalists, bloggers, editors) | 1 | 33% |
Mendeley readers
The data shown below were compiled from readership statistics for 52 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 52 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 12 | 23% |
| Researcher | 7 | 13% |
| Student > Bachelor | 6 | 12% |
| Student > Doctoral Student | 4 | 8% |
| Student > Master | 4 | 8% |
| Other | 8 | 15% |
| Unknown | 11 | 21% |
| Readers by discipline | Count | As % |
|---|---|---|
| Medicine and Dentistry | 12 | 23% |
| Computer Science | 10 | 19% |
| Engineering | 4 | 8% |
| Agricultural and Biological Sciences | 4 | 8% |
| Biochemistry, Genetics and Molecular Biology | 1 | 2% |
| Other | 6 | 12% |
| Unknown | 15 | 29% |
Attention Score in Context
This research output has an Altmetric Attention Score of 13. 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 12 November 2021.
All research outputs
#2,456,984
of 23,416,487 outputs
Outputs from BMC Complementary Medicine and Therapies
#453
of 3,689 outputs
Outputs of similar age
#14,768
of 150,464 outputs
Outputs of similar age from BMC Complementary Medicine and Therapies
#14
of 68 outputs
Altmetric has tracked 23,416,487 research outputs across all sources so far. Compared to these this one has done well and is in the 89th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 3,689 research outputs from this source. They typically receive more attention than average, with a mean Attention Score of 8.9. This one has done well, scoring higher than 87% 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 150,464 tracked outputs that were published within six weeks on either side of this one in any source. This one has done particularly well, scoring higher than 90% of its contemporaries.
We're also able to compare this research output to 68 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 80% of its contemporaries.