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Mendeley readers
| Title |
BIOADI: a machine learning approach to identifying abbreviations and definitions in biological literature
|
|---|---|
| Published in |
BMC Bioinformatics, December 2009
|
| DOI | 10.1186/1471-2105-10-s15-s7 |
| Pubmed ID | |
| Authors |
Cheng-Ju Kuo, Maurice HT Ling, Kuan-Ting Lin, Chun-Nan Hsu |
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 % |
|---|---|---|
| United Kingdom | 1 | 2% |
| Spain | 1 | 2% |
| Austria | 1 | 2% |
| Unknown | 49 | 94% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Researcher | 8 | 15% |
| Student > Bachelor | 8 | 15% |
| Student > Ph. D. Student | 7 | 13% |
| Student > Master | 6 | 12% |
| Student > Doctoral Student | 3 | 6% |
| Other | 7 | 13% |
| Unknown | 13 | 25% |
| Readers by discipline | Count | As % |
|---|---|---|
| Computer Science | 20 | 38% |
| Agricultural and Biological Sciences | 5 | 10% |
| Medicine and Dentistry | 4 | 8% |
| Engineering | 3 | 6% |
| Linguistics | 2 | 4% |
| Other | 3 | 6% |
| Unknown | 15 | 29% |