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Mendeley readers
| Title |
Comparison of machine-learning algorithms to build a predictive model for detecting undiagnosed diabetes - ELSA-Brasil: accuracy study
|
|---|---|
| Published in |
Sao Paulo Medical Journal, April 2017
|
| DOI | 10.1590/1516-3180.2016.0309010217 |
| Pubmed ID | |
| Authors |
André Rodrigues Olivera, Valter Roesler, Cirano Iochpe, Maria Inês Schmidt, Álvaro Vigo, Sandhi Maria Barreto, Bruce Bartholow Duncan |
Mendeley readers
The data shown below were compiled from readership statistics for 69 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 69 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Master | 11 | 16% |
| Student > Ph. D. Student | 10 | 14% |
| Student > Bachelor | 7 | 10% |
| Student > Doctoral Student | 6 | 9% |
| Researcher | 5 | 7% |
| Other | 6 | 9% |
| Unknown | 24 | 35% |
| Readers by discipline | Count | As % |
|---|---|---|
| Computer Science | 17 | 25% |
| Engineering | 13 | 19% |
| Mathematics | 3 | 4% |
| Nursing and Health Professions | 2 | 3% |
| Psychology | 2 | 3% |
| Other | 8 | 12% |
| Unknown | 24 | 35% |