You are seeing a free-to-access but limited selection of the activity Altmetric has collected about this research output.
Click here to find out more.
Mendeley readers
Chapter title |
Reducing Annotation Need in Self-explanatory Models for Lung Nodule Diagnosis
|
---|---|
Chapter number | 4 |
Book title |
Interpretability of Machine Intelligence in Medical Image Computing
|
Published by |
Springer, Cham, January 2022
|
DOI | 10.1007/978-3-031-17976-1_4 |
Book ISBNs |
978-3-03-117975-4, 978-3-03-117976-1
|
Authors |
Lu, Jiahao, Yin, Chong, Krause, Oswin, Erleben, Kenny, Nielsen, Michael Bachmann, Darkner, Sune |
Mendeley readers
The data shown below were compiled from readership statistics for 6 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
Country | Count | As % |
---|---|---|
Unknown | 6 | 100% |
Demographic breakdown
Readers by professional status | Count | As % |
---|---|---|
Other | 1 | 17% |
Professor | 1 | 17% |
Researcher | 1 | 17% |
Student > Master | 1 | 17% |
Unknown | 2 | 33% |
Readers by discipline | Count | As % |
---|---|---|
Medicine and Dentistry | 2 | 33% |
Physics and Astronomy | 1 | 17% |
Unknown | 3 | 50% |