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Mendeley readers
| Title |
A Probabilistic Model for Early Prediction of Abnormal Clinical Events Using Vital Sign Correlations in Home-Based Monitoring
|
|---|---|
| Published by |
Institute of Electrical and Electronics Engineers (IEEE), March 2016
|
| DOI | 10.1109/percom.2016.7456519 |
| Authors |
Abdur Rahim Mohammad Forkan, Ibrahim Khalil |
Mendeley readers
The data shown below were compiled from readership statistics for 63 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Korea, Republic of | 1 | 2% |
| Unknown | 62 | 98% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 13 | 21% |
| Student > Master | 10 | 16% |
| Researcher | 7 | 11% |
| Student > Bachelor | 5 | 8% |
| Student > Doctoral Student | 4 | 6% |
| Other | 12 | 19% |
| Unknown | 12 | 19% |
| Readers by discipline | Count | As % |
|---|---|---|
| Computer Science | 24 | 38% |
| Engineering | 12 | 19% |
| Medicine and Dentistry | 3 | 5% |
| Nursing and Health Professions | 2 | 3% |
| Business, Management and Accounting | 2 | 3% |
| Other | 6 | 10% |
| Unknown | 14 | 22% |