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.
X Demographics
Mendeley readers
| Title |
Machine learning techniques for computer-aided classification of active inflammatory sacroiliitis in magnetic resonance imaging
|
|---|---|
| Published in |
Advances in Rheumatology, May 2020
|
| DOI | 10.1186/s42358-020-00126-8 |
| Pubmed ID | |
| Authors |
Matheus Calil Faleiros, Marcello Henrique Nogueira-Barbosa, Vitor Faeda Dalto, José Raniery Ferreira Júnior, Ariane Priscilla Magalhães Tenório, Rodrigo Luppino-Assad, Paulo Louzada-Junior, Rangaraj Mandayam Rangayyan, Paulo Mazzoncini de Azevedo-Marques |
X Demographics
The data shown below were collected from the profiles of 4 X users who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Spain | 2 | 50% |
| Brazil | 1 | 25% |
| Netherlands | 1 | 25% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 2 | 50% |
| Practitioners (doctors, other healthcare professionals) | 2 | 50% |
Mendeley readers
The data shown below were compiled from readership statistics for 58 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 58 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Bachelor | 7 | 12% |
| Student > Ph. D. Student | 5 | 9% |
| Lecturer | 4 | 7% |
| Other | 3 | 5% |
| Unspecified | 3 | 5% |
| Other | 7 | 12% |
| Unknown | 29 | 50% |
| Readers by discipline | Count | As % |
|---|---|---|
| Computer Science | 9 | 16% |
| Medicine and Dentistry | 6 | 10% |
| Unspecified | 3 | 5% |
| Biochemistry, Genetics and Molecular Biology | 2 | 3% |
| Engineering | 2 | 3% |
| Other | 6 | 10% |
| Unknown | 30 | 52% |