The data shown below were compiled from readership statistics for 28 Mendeley readers of this research output. Click here to see the associated Mendeley record.
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Mendeley readers
| Title |
Machine-learning model predicting postoperative delirium in older patients using intraoperative frontal electroencephalographic signatures
|
|---|---|
| Published in |
Frontiers in Aging Neuroscience, October 2022
|
| DOI | 10.3389/fnagi.2022.911088 |
| Pubmed ID | |
| Authors |
Vera Röhr, Benjamin Blankertz, Finn M. Radtke, Claudia Spies, Susanne Koch |
Mendeley readers
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 28 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Researcher | 5 | 18% |
| Student > Ph. D. Student | 4 | 14% |
| Other | 1 | 4% |
| Lecturer | 1 | 4% |
| Student > Bachelor | 1 | 4% |
| Other | 3 | 11% |
| Unknown | 13 | 46% |
| Readers by discipline | Count | As % |
|---|---|---|
| Medicine and Dentistry | 8 | 29% |
| Neuroscience | 3 | 11% |
| Nursing and Health Professions | 1 | 4% |
| Pharmacology, Toxicology and Pharmaceutical Science | 1 | 4% |
| Business, Management and Accounting | 1 | 4% |
| Other | 1 | 4% |
| Unknown | 13 | 46% |