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| Chapter title |
Advances in Intelligent Based Internet of Medical Things (IoMT) for COVID-19: Olfactory Disorders
|
|---|---|
| Chapter number | 19 |
| Book title |
Computational Intelligence Methods in COVID-19: Surveillance, Prevention, Prediction and Diagnosis
|
| Published by |
Springer, Singapore, October 2020
|
| DOI | 10.1007/978-981-15-8534-0_19 |
| Book ISBNs |
978-9-81-158533-3, 978-9-81-158534-0
|
| Authors |
V. Evelyn Brindha, X. Anitha Mary, Evelyn Brindha, V., Anitha Mary, X. |
Mendeley readers
The data shown below were compiled from readership statistics for 21 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 21 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Researcher | 4 | 19% |
| Professor | 3 | 14% |
| Student > Doctoral Student | 2 | 10% |
| Lecturer > Senior Lecturer | 2 | 10% |
| Professor > Associate Professor | 2 | 10% |
| Other | 5 | 24% |
| Unknown | 3 | 14% |
| Readers by discipline | Count | As % |
|---|---|---|
| Computer Science | 4 | 19% |
| Engineering | 3 | 14% |
| Medicine and Dentistry | 3 | 14% |
| Biochemistry, Genetics and Molecular Biology | 2 | 10% |
| Social Sciences | 2 | 10% |
| Other | 5 | 24% |
| Unknown | 2 | 10% |