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Twitter Demographics
Mendeley readers
Chapter title |
Physiological Parameter Estimation from Multispectral Images Unleashed
|
---|---|
Chapter number | 16 |
Book title |
Medical Image Computing and Computer-Assisted Intervention − MICCAI 2017
|
Published by |
Springer, Cham, September 2017
|
DOI | 10.1007/978-3-319-66179-7_16 |
Book ISBNs |
978-3-31-966178-0, 978-3-31-966179-7
|
Authors |
Sebastian J. Wirkert, Anant S. Vemuri, Hannes G. Kenngott, Sara Moccia, Michael Götz, Benjamin F. B. Mayer, Klaus H. Maier-Hein, Daniel S. Elson, Lena Maier-Hein |
Twitter Demographics
The data shown below were collected from the profiles of 2 tweeters who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
Country | Count | As % |
---|---|---|
Germany | 1 | 50% |
Unknown | 1 | 50% |
Demographic breakdown
Type | Count | As % |
---|---|---|
Scientists | 2 | 100% |
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 % |
---|---|---|
Student > Ph. D. Student | 6 | 29% |
Professor > Associate Professor | 3 | 14% |
Researcher | 3 | 14% |
Student > Master | 2 | 10% |
Other | 2 | 10% |
Other | 1 | 5% |
Unknown | 4 | 19% |
Readers by discipline | Count | As % |
---|---|---|
Computer Science | 8 | 38% |
Engineering | 3 | 14% |
Agricultural and Biological Sciences | 1 | 5% |
Mathematics | 1 | 5% |
Medicine and Dentistry | 1 | 5% |
Other | 1 | 5% |
Unknown | 6 | 29% |