| Title |
Machine learning methods for the study of cybersickness: a systematic review
|
|---|---|
| Published in |
Brain Informatics, October 2022
|
| DOI | 10.1186/s40708-022-00172-6 |
| Pubmed ID | |
| Authors |
Alexander Hui Xiang Yang, Nikola Kasabov, Yusuf Ozgur Cakmak |
Mendeley readers
The data shown below were compiled from readership statistics for 64 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 64 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 9 | 14% |
| Researcher | 7 | 11% |
| Professor > Associate Professor | 4 | 6% |
| Student > Bachelor | 3 | 5% |
| Student > Doctoral Student | 2 | 3% |
| Other | 9 | 14% |
| Unknown | 30 | 47% |
| Readers by discipline | Count | As % |
|---|---|---|
| Computer Science | 9 | 14% |
| Medicine and Dentistry | 4 | 6% |
| Engineering | 4 | 6% |
| Business, Management and Accounting | 3 | 5% |
| Nursing and Health Professions | 3 | 5% |
| Other | 8 | 13% |
| Unknown | 33 | 52% |