Uncertainty for Safe Utilization of Machine Learning in Medical Imaging, and Graphs in Biomedical…
Springer International Publishing
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.
| 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 |
Twitter Demographics
The data shown below were collected from the profiles of 16 tweeters who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Switzerland | 7 | 44% |
| United Kingdom | 3 | 19% |
| Spain | 1 | 6% |
| Singapore | 1 | 6% |
| Unknown | 4 | 25% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Scientists | 9 | 56% |
| Members of the public | 6 | 38% |
| Practitioners (doctors, other healthcare professionals) | 1 | 6% |
Mendeley readers
The data shown below were compiled from readership statistics for 28 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 28 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Researcher | 6 | 21% |
| Student > Master | 4 | 14% |
| Student > Bachelor | 4 | 14% |
| Other | 2 | 7% |
| Student > Ph. D. Student | 2 | 7% |
| Other | 4 | 14% |
| Unknown | 6 | 21% |
| Readers by discipline | Count | As % |
|---|---|---|
| Computer Science | 9 | 32% |
| Biochemistry, Genetics and Molecular Biology | 4 | 14% |
| Medicine and Dentistry | 4 | 14% |
| Engineering | 2 | 7% |
| Physics and Astronomy | 1 | 4% |
| Other | 1 | 4% |
| Unknown | 7 | 25% |