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X Demographics
Mendeley readers
Attention Score in Context
| Title |
Using an artificial neural network to map cancer common data elements to the biomedical research integrated domain group model in a semi-automated manner
|
|---|---|
| Published in |
BMC Medical Informatics and Decision Making, December 2019
|
| DOI | 10.1186/s12911-019-0979-5 |
| Pubmed ID | |
| Authors |
Robinette Renner, Shengyu Li, Yulong Huang, Ada Chaeli van der Zijp-Tan, Shaobo Tan, Dongqi Li, Mohan Vamsi Kasukurthi, Ryan Benton, Glen M. Borchert, Jingshan Huang, Guoqian Jiang |
X Demographics
The data shown below were collected from the profiles of 5 X users who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United States | 1 | 20% |
| India | 1 | 20% |
| France | 1 | 20% |
| Unknown | 2 | 40% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 5 | 100% |
Mendeley readers
The data shown below were compiled from readership statistics for 17 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 17 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Professor > Associate Professor | 3 | 18% |
| Researcher | 3 | 18% |
| Other | 2 | 12% |
| Student > Ph. D. Student | 2 | 12% |
| Student > Master | 2 | 12% |
| Other | 2 | 12% |
| Unknown | 3 | 18% |
| Readers by discipline | Count | As % |
|---|---|---|
| Computer Science | 3 | 18% |
| Biochemistry, Genetics and Molecular Biology | 2 | 12% |
| Medicine and Dentistry | 2 | 12% |
| Nursing and Health Professions | 1 | 6% |
| Agricultural and Biological Sciences | 1 | 6% |
| Other | 4 | 24% |
| Unknown | 4 | 24% |
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 25 December 2019.
All research outputs
#13,665,876
of 23,184,056 outputs
Outputs from BMC Medical Informatics and Decision Making
#1,003
of 2,016 outputs
Outputs of similar age
#222,984
of 457,757 outputs
Outputs of similar age from BMC Medical Informatics and Decision Making
#33
of 68 outputs
Altmetric has tracked 23,184,056 research outputs across all sources so far. This one is in the 39th percentile – i.e., 39% of other outputs scored the same or lower than it.
So far Altmetric has tracked 2,016 research outputs from this source. They receive a mean Attention Score of 4.9. This one is in the 47th percentile – i.e., 47% 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 457,757 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 49th percentile – i.e., 49% of its contemporaries scored the same or lower than it.
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 is in the 48th percentile – i.e., 48% of its contemporaries scored the same or lower than it.