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X Demographics
Mendeley readers
Title |
Multi_Scale_Tools: A Python Library to Exploit Multi-Scale Whole Slide Images
|
---|---|
Published in |
Frontiers in Computer Science, August 2021
|
DOI | 10.3389/fcomp.2021.684521 |
Authors |
Niccolò Marini, Sebastian Otálora, Damian Podareanu, Mart van Rijthoven, Jeroen van der Laak, Francesco Ciompi, Henning Müller, Manfredo Atzori |
X Demographics
The data shown below were collected from the profiles of 3 X users who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
Country | Count | As % |
---|---|---|
Switzerland | 2 | 67% |
Unknown | 1 | 33% |
Demographic breakdown
Type | Count | As % |
---|---|---|
Members of the public | 3 | 100% |
Mendeley readers
The data shown below were compiled from readership statistics for 29 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
Country | Count | As % |
---|---|---|
Unknown | 29 | 100% |
Demographic breakdown
Readers by professional status | Count | As % |
---|---|---|
Student > Doctoral Student | 4 | 14% |
Researcher | 3 | 10% |
Student > Ph. D. Student | 2 | 7% |
Lecturer | 1 | 3% |
Student > Bachelor | 1 | 3% |
Other | 4 | 14% |
Unknown | 14 | 48% |
Readers by discipline | Count | As % |
---|---|---|
Computer Science | 7 | 24% |
Engineering | 6 | 21% |
Medicine and Dentistry | 2 | 7% |
Nursing and Health Professions | 1 | 3% |
Unknown | 13 | 45% |