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X Demographics
Title |
Interpretable and Annotation-Efficient Learning for Medical Image Computing
|
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Published by |
Springer International Publishing, January 2020
|
DOI | 10.1007/978-3-030-61166-8 |
ISBNs |
978-3-03-061165-1, 978-3-03-061166-8
|
Editors |
Jaime Cardoso, Hien Van Nguyen, Nicholas Heller, Pedro Henriques Abreu, Ivana Isgum, Wilson Silva, Ricardo Cruz, Jose Pereira Amorim, Vishal Patel, Badri Roysam, Kevin Zhou, Steve Jiang, Ngan Le, Khoa Luu, Raphael Sznitman, Veronika Cheplygina, Diana Mateus, Emanuele Trucco, Samaneh Abbasi |
X Demographics
The data shown below were collected from the profiles of 21 X users who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
Country | Count | As % |
---|---|---|
France | 5 | 24% |
United Kingdom | 2 | 10% |
United States | 1 | 5% |
Netherlands | 1 | 5% |
Switzerland | 1 | 5% |
Japan | 1 | 5% |
Unknown | 10 | 48% |
Demographic breakdown
Type | Count | As % |
---|---|---|
Members of the public | 13 | 62% |
Scientists | 4 | 19% |
Practitioners (doctors, other healthcare professionals) | 4 | 19% |