| Title |
Glaucomatous Patterns in Frequency Doubling Technology (FDT) Perimetry Data Identified by Unsupervised Machine Learning Classifiers
|
|---|---|
| Published in |
PLOS ONE, January 2014
|
| DOI | 10.1371/journal.pone.0085941 |
| Pubmed ID | |
| Authors |
Christopher Bowd, Robert N. Weinreb, Madhusudhanan Balasubramanian, Intae Lee, Giljin Jang, Siamak Yousefi, Linda M. Zangwill, Felipe A. Medeiros, Christopher A. Girkin, Jeffrey M. Liebmann, Michael H. Goldbaum |
Mendeley readers
The data shown below were compiled from readership statistics for 46 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 46 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Other | 6 | 13% |
| Student > Ph. D. Student | 6 | 13% |
| Student > Bachelor | 5 | 11% |
| Professor | 4 | 9% |
| Student > Postgraduate | 4 | 9% |
| Other | 8 | 17% |
| Unknown | 13 | 28% |
| Readers by discipline | Count | As % |
|---|---|---|
| Medicine and Dentistry | 17 | 37% |
| Computer Science | 6 | 13% |
| Agricultural and Biological Sciences | 2 | 4% |
| Engineering | 2 | 4% |
| Physics and Astronomy | 1 | 2% |
| Other | 2 | 4% |
| Unknown | 16 | 35% |