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Mendeley readers
| Title |
Electronic health records accurately predict renal replacement therapy in acute kidney injury
|
|---|---|
| Published in |
BMC Nephrology, January 2019
|
| DOI | 10.1186/s12882-019-1206-4 |
| Pubmed ID | |
| Authors |
Sanmay Low, Anantharaman Vathsala, Tanusya Murali Murali, Long Pang, Graeme MacLaren, Wan-Ying Ng, Sabrina Haroon, Amartya Mukhopadhyay, Shir-Lynn Lim, Bee-Hong Tan, Titus Lau, Horng-Ruey Chua |
Mendeley readers
The data shown below were compiled from readership statistics for 60 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 60 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Bachelor | 10 | 17% |
| Researcher | 9 | 15% |
| Student > Master | 8 | 13% |
| Student > Doctoral Student | 3 | 5% |
| Student > Ph. D. Student | 3 | 5% |
| Other | 7 | 12% |
| Unknown | 20 | 33% |
| Readers by discipline | Count | As % |
|---|---|---|
| Medicine and Dentistry | 22 | 37% |
| Nursing and Health Professions | 5 | 8% |
| Engineering | 3 | 5% |
| Psychology | 2 | 3% |
| Business, Management and Accounting | 1 | 2% |
| Other | 6 | 10% |
| Unknown | 21 | 35% |