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X Demographics
Mendeley readers
| Title |
Assessment of the implementation context in preparation for a clinical study of machine-learning algorithms to automate the classification of digital cervical images for cervical cancer screening in resource-constrained settings
|
|---|---|
| Published in |
Frontiers in Health Services, September 2022
|
| DOI | 10.3389/frhs.2022.1000150 |
| Pubmed ID | |
| Authors |
Delivette Castor, Rakiya Saidu, Rosalind Boa, Nomonde Mbatani, Tinashe E. M. Mutsvangwa, Jennifer Moodley, Lynette Denny, Louise Kuhn |
X Demographics
The data shown below were collected from the profiles of 8 X users who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| South Africa | 2 | 25% |
| United Kingdom | 1 | 13% |
| United States | 1 | 13% |
| Singapore | 1 | 13% |
| Switzerland | 1 | 13% |
| Unknown | 2 | 25% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 3 | 38% |
| Scientists | 3 | 38% |
| Practitioners (doctors, other healthcare professionals) | 2 | 25% |
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 % |
|---|---|---|
| Student > Ph. D. Student | 2 | 13% |
| Researcher | 2 | 13% |
| Student > Postgraduate | 1 | 7% |
| Unknown | 10 | 67% |
| Readers by discipline | Count | As % |
|---|---|---|
| Medicine and Dentistry | 4 | 27% |
| Engineering | 1 | 7% |
| Unknown | 10 | 67% |