Medical Image Computing and Computer Assisted Intervention – MICCAI 2021
Springer International Publishing
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X Demographics
Mendeley readers
| Chapter title |
Detecting When Pre-trained nnU-Net Models Fail Silently for Covid-19 Lung Lesion Segmentation
|
|---|---|
| Book title |
Medical Image Computing and Computer Assisted Intervention – MICCAI 2021
|
| Published by |
Springer, Cham, September 2021
|
| DOI | 10.1007/978-3-030-87234-2_29 |
| Book ISBNs |
978-3-03-087233-5, 978-3-03-087234-2
|
| Authors |
Gonzalez, Camila, Gotkowski, Karol, Bucher, Andreas, Fischbach, Ricarda, Kaltenborn, Isabel, Mukhopadhyay, Anirban |
X Demographics
The data shown below were collected from the profile of 1 X user who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United States | 1 | 100% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Scientists | 1 | 100% |
Mendeley readers
The data shown below were compiled from readership statistics for 35 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 35 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 10 | 29% |
| Student > Doctoral Student | 2 | 6% |
| Researcher | 2 | 6% |
| Student > Bachelor | 2 | 6% |
| Student > Master | 2 | 6% |
| Other | 2 | 6% |
| Unknown | 15 | 43% |
| Readers by discipline | Count | As % |
|---|---|---|
| Computer Science | 12 | 34% |
| Engineering | 2 | 6% |
| Philosophy | 1 | 3% |
| Agricultural and Biological Sciences | 1 | 3% |
| Mathematics | 1 | 3% |
| Other | 2 | 6% |
| Unknown | 16 | 46% |