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Mendeley readers
| Title |
Incorporating tumour pathology information into breast cancer risk prediction algorithms
|
|---|---|
| Published in |
Breast Cancer Research, May 2010
|
| DOI | 10.1186/bcr2576 |
| Pubmed ID | |
| Authors |
Nasim Mavaddat, Timothy R Rebbeck, Sunil R Lakhani, Douglas F Easton, Antonis C Antoniou |
Mendeley readers
The data shown below were compiled from readership statistics for 71 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United Kingdom | 2 | 3% |
| Uruguay | 1 | 1% |
| Canada | 1 | 1% |
| Unknown | 67 | 94% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Researcher | 14 | 20% |
| Student > Ph. D. Student | 12 | 17% |
| Other | 7 | 10% |
| Student > Doctoral Student | 6 | 8% |
| Student > Master | 5 | 7% |
| Other | 12 | 17% |
| Unknown | 15 | 21% |
| Readers by discipline | Count | As % |
|---|---|---|
| Medicine and Dentistry | 30 | 42% |
| Agricultural and Biological Sciences | 8 | 11% |
| Biochemistry, Genetics and Molecular Biology | 8 | 11% |
| Computer Science | 3 | 4% |
| Mathematics | 2 | 3% |
| Other | 6 | 8% |
| Unknown | 14 | 20% |