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Mendeley readers
Chapter title |
Interpretable Deep Neural Network to Predict Estrogen Receptor Status from Haematoxylin-Eosin Images
|
---|---|
Chapter number | 2 |
Book title |
Artificial Intelligence and Machine Learning for Digital Pathology
|
Published by |
Springer, Cham, January 2020
|
DOI | 10.1007/978-3-030-50402-1_2 |
Book ISBNs |
978-3-03-050401-4, 978-3-03-050402-1
|
Authors |
Philipp Seegerer, Alexander Binder, René Saitenmacher, Michael Bockmayr, Maximilian Alber, Philipp Jurmeister, Frederick Klauschen, Klaus-Robert Müller |
Mendeley readers
The data shown below were compiled from readership statistics for 17 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
Country | Count | As % |
---|---|---|
Unknown | 17 | 100% |
Demographic breakdown
Readers by professional status | Count | As % |
---|---|---|
Researcher | 3 | 18% |
Student > Doctoral Student | 3 | 18% |
Unknown | 11 | 65% |
Readers by discipline | Count | As % |
---|---|---|
Computer Science | 1 | 6% |
Agricultural and Biological Sciences | 1 | 6% |
Medicine and Dentistry | 1 | 6% |
Engineering | 1 | 6% |
Unknown | 13 | 76% |