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Mendeley readers
| Title |
Automatically detecting Crohn’s disease and Ulcerative Colitis from endoscopic imaging
|
|---|---|
| Published in |
BMC Medical Informatics and Decision Making, November 2022
|
| DOI | 10.1186/s12911-022-02043-w |
| Pubmed ID | |
| Authors |
Marco Chierici, Nicolae Puica, Matteo Pozzi, Antonello Capistrano, Marcello Dorian Donzella, Antonio Colangelo, Venet Osmani, Giuseppe Jurman |
Mendeley readers
The data shown below were compiled from readership statistics for 15 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 15 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Researcher | 3 | 20% |
| Lecturer | 1 | 7% |
| Librarian | 1 | 7% |
| Student > Master | 1 | 7% |
| Student > Bachelor | 1 | 7% |
| Other | 0 | 0% |
| Unknown | 8 | 53% |
| Readers by discipline | Count | As % |
|---|---|---|
| Medicine and Dentistry | 2 | 13% |
| Computer Science | 1 | 7% |
| Nursing and Health Professions | 1 | 7% |
| Physics and Astronomy | 1 | 7% |
| Engineering | 1 | 7% |
| Other | 0 | 0% |
| Unknown | 9 | 60% |