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X Demographics
Mendeley readers
| Chapter title |
HACT-Net: A Hierarchical Cell-to-Tissue Graph Neural Network for Histopathological Image Classification
|
|---|---|
| Chapter number | 20 |
| Book title |
Uncertainty for Safe Utilization of Machine Learning in Medical Imaging, and Graphs in Biomedical Image Analysis
|
| Published by |
Springer, Cham, October 2020
|
| DOI | 10.1007/978-3-030-60365-6_20 |
| Book ISBNs |
978-3-03-060364-9, 978-3-03-060365-6
|
| Authors |
Pushpak Pati, Guillaume Jaume, Lauren Alisha Fernandes, Antonio Foncubierta-Rodríguez, Florinda Feroce, Anna Maria Anniciello, Giosue Scognamiglio, Nadia Brancati, Daniel Riccio, Maurizio Di Bonito, Giuseppe De Pietro, Gerardo Botti, Orcun Goksel, Jean-Philippe Thiran, Maria Frucci, Maria Gabrani |
X Demographics
The data shown below were collected from the profiles of 15 X users who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Switzerland | 4 | 27% |
| United Kingdom | 3 | 20% |
| Canada | 1 | 7% |
| Singapore | 1 | 7% |
| United States | 1 | 7% |
| Spain | 1 | 7% |
| Unknown | 4 | 27% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Scientists | 9 | 60% |
| Members of the public | 5 | 33% |
| Practitioners (doctors, other healthcare professionals) | 1 | 7% |
Mendeley readers
The data shown below were compiled from readership statistics for 81 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 81 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Master | 10 | 12% |
| Researcher | 9 | 11% |
| Student > Ph. D. Student | 7 | 9% |
| Student > Bachelor | 6 | 7% |
| Student > Doctoral Student | 3 | 4% |
| Other | 11 | 14% |
| Unknown | 35 | 43% |
| Readers by discipline | Count | As % |
|---|---|---|
| Computer Science | 25 | 31% |
| Engineering | 8 | 10% |
| Medicine and Dentistry | 5 | 6% |
| Biochemistry, Genetics and Molecular Biology | 4 | 5% |
| Mathematics | 1 | 1% |
| Other | 5 | 6% |
| Unknown | 33 | 41% |