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Mendeley readers
| Title |
1842676957299765Latent class cluster analysis to understand heterogeneity in prostate cancer treatment utilities
|
|---|---|
| Published in |
BMC Medical Informatics and Decision Making, November 2009
|
| DOI | 10.1186/1472-6947-9-47 |
| Pubmed ID | |
| Authors |
Salimah H Meghani, Christopher S Lee, Alexandra L Hanlon, Deborah W Bruner |
Mendeley readers
The data shown below were compiled from readership statistics for 93 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Canada | 5 | 5% |
| Switzerland | 1 | 1% |
| Turkey | 1 | 1% |
| Uganda | 1 | 1% |
| Germany | 1 | 1% |
| United Kingdom | 1 | 1% |
| Denmark | 1 | 1% |
| Spain | 1 | 1% |
| United States | 1 | 1% |
| Other | 0 | 0% |
| Unknown | 80 | 86% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 21 | 23% |
| Researcher | 20 | 22% |
| Student > Master | 11 | 12% |
| Other | 8 | 9% |
| Professor > Associate Professor | 7 | 8% |
| Other | 22 | 24% |
| Unknown | 4 | 4% |
| Readers by discipline | Count | As % |
|---|---|---|
| Medicine and Dentistry | 19 | 20% |
| Psychology | 11 | 12% |
| Social Sciences | 8 | 9% |
| Nursing and Health Professions | 6 | 6% |
| Computer Science | 6 | 6% |
| Other | 28 | 30% |
| Unknown | 15 | 16% |