Medical Image Computing and Computer Assisted Intervention – MICCAI 2018
Springer International Publishing
Chapter title |
Towards Safe Deep Learning: Accurately Quantifying Biomarker Uncertainty in Neural Network Predictions
|
---|---|
Chapter number | 78 |
Book title |
Medical Image Computing and Computer Assisted Intervention – MICCAI 2018
|
Published by |
Springer, Cham, September 2018
|
DOI | 10.1007/978-3-030-00928-1_78 |
Book ISBNs |
978-3-03-000927-4, 978-3-03-000928-1
|
Authors |
Zach Eaton-Rosen, Felix Bragman, Sotirios Bisdas, Sébastien Ourselin, M. Jorge Cardoso |
Country | Count | As % |
---|---|---|
United States | 1 | 50% |
Unknown | 1 | 50% |
Type | Count | As % |
---|---|---|
Members of the public | 1 | 50% |
Scientists | 1 | 50% |
Country | Count | As % |
---|---|---|
Unknown | 83 | 100% |
Readers by professional status | Count | As % |
---|---|---|
Student > Ph. D. Student | 25 | 30% |
Student > Master | 13 | 16% |
Researcher | 7 | 8% |
Student > Doctoral Student | 2 | 2% |
Other | 2 | 2% |
Other | 7 | 8% |
Unknown | 27 | 33% |
Readers by discipline | Count | As % |
---|---|---|
Computer Science | 24 | 29% |
Engineering | 18 | 22% |
Physics and Astronomy | 4 | 5% |
Mathematics | 3 | 4% |
Agricultural and Biological Sciences | 1 | 1% |
Other | 3 | 4% |
Unknown | 30 | 36% |