| Title |
Machine learning can classify vital sign alerts as real or artifact in online continuous monitoring data
|
|---|---|
| Published in |
Intensive Care Medicine Experimental, October 2015
|
| DOI | 10.1186/2197-425x-3-s1-a550 |
| Pubmed ID | |
| Authors |
M Hravnak, L Chen, A Dubrawski, D Wang, E Bose, G Clermont, AM Kaynar, D Wallace, A Holder, MR Pinsky |
Mendeley readers
The data shown below were compiled from readership statistics for 8 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 8 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Other | 2 | 25% |
| Researcher | 1 | 13% |
| Student > Doctoral Student | 1 | 13% |
| Student > Bachelor | 1 | 13% |
| Student > Ph. D. Student | 1 | 13% |
| Other | 1 | 13% |
| Unknown | 1 | 13% |
| Readers by discipline | Count | As % |
|---|---|---|
| Engineering | 2 | 25% |
| Computer Science | 1 | 13% |
| Business, Management and Accounting | 1 | 13% |
| Medicine and Dentistry | 1 | 13% |
| Earth and Planetary Sciences | 1 | 13% |
| Other | 0 | 0% |
| Unknown | 2 | 25% |