You are seeing a free-to-access but limited selection of the activity Altmetric has collected about this research output.
Click here to find out more.
X Demographics
Mendeley readers
Attention Score in Context
| Title |
Novel image markers for non-small cell lung cancer classification and survival prediction
|
|---|---|
| Published in |
BMC Bioinformatics, September 2014
|
| DOI | 10.1186/1471-2105-15-310 |
| Pubmed ID | |
| Authors |
Hongyuan Wang, Fuyong Xing, Hai Su, Arnold Stromberg, Lin Yang |
| Abstract |
Non-small cell lung cancer (NSCLC), the most common type of lung cancer, is one of serious diseases causing death for both men and women. Computer-aided diagnosis and survival prediction of NSCLC, is of great importance in providing assistance to diagnosis and personalize therapy planning for lung cancer patients. |
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 % |
|---|---|---|
| Unknown | 1 | 100% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Scientists | 1 | 100% |
Mendeley readers
The data shown below were compiled from readership statistics for 86 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Iran, Islamic Republic of | 1 | 1% |
| United Kingdom | 1 | 1% |
| Brazil | 1 | 1% |
| Unknown | 83 | 97% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 20 | 23% |
| Student > Master | 18 | 21% |
| Researcher | 8 | 9% |
| Other | 5 | 6% |
| Student > Bachelor | 4 | 5% |
| Other | 17 | 20% |
| Unknown | 14 | 16% |
| Readers by discipline | Count | As % |
|---|---|---|
| Computer Science | 32 | 37% |
| Medicine and Dentistry | 12 | 14% |
| Engineering | 7 | 8% |
| Agricultural and Biological Sciences | 6 | 7% |
| Biochemistry, Genetics and Molecular Biology | 4 | 5% |
| Other | 9 | 10% |
| Unknown | 16 | 19% |
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 19 September 2014.
All research outputs
#20,237,640
of 22,764,165 outputs
Outputs from BMC Bioinformatics
#6,845
of 7,273 outputs
Outputs of similar age
#209,067
of 250,225 outputs
Outputs of similar age from BMC Bioinformatics
#102
of 111 outputs
Altmetric has tracked 22,764,165 research outputs across all sources so far. This one is in the 1st percentile – i.e., 1% of other outputs scored the same or lower than it.
So far Altmetric has tracked 7,273 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 5.4. This one is in the 1st percentile – i.e., 1% 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 250,225 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 1st percentile – i.e., 1% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 111 others from the same source and published within six weeks on either side of this one. This one is in the 1st percentile – i.e., 1% of its contemporaries scored the same or lower than it.