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Mendeley readers
| Title |
Supporting the annotation of chronic obstructive pulmonary disease (COPD) phenotypes with text mining workflows
|
|---|---|
| Published in |
Journal of Biomedical Semantics, March 2015
|
| DOI | 10.1186/s13326-015-0004-6 |
| Pubmed ID | |
| Authors |
Xiao Fu, Riza Batista-Navarro, Rafal Rak, Sophia Ananiadou |
Mendeley readers
The data shown below were compiled from readership statistics for 55 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Germany | 1 | 2% |
| Brazil | 1 | 2% |
| India | 1 | 2% |
| Denmark | 1 | 2% |
| Spain | 1 | 2% |
| Unknown | 50 | 91% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Researcher | 12 | 22% |
| Student > Ph. D. Student | 8 | 15% |
| Student > Bachelor | 5 | 9% |
| Student > Master | 4 | 7% |
| Professor | 3 | 5% |
| Other | 12 | 22% |
| Unknown | 11 | 20% |
| Readers by discipline | Count | As % |
|---|---|---|
| Computer Science | 13 | 24% |
| Medicine and Dentistry | 9 | 16% |
| Biochemistry, Genetics and Molecular Biology | 4 | 7% |
| Engineering | 4 | 7% |
| Agricultural and Biological Sciences | 4 | 7% |
| Other | 10 | 18% |
| Unknown | 11 | 20% |