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X Demographics
Mendeley readers
| Title |
Addressing Fairness, Bias, and Appropriate Use of Artificial Intelligence and Machine Learning in Global Health
|
|---|---|
| Published in |
Frontiers in Artificial Intelligence, April 2021
|
| DOI | 10.3389/frai.2020.561802 |
| Pubmed ID | |
| Authors |
Richard Ribón Fletcher, Audace Nakeshimana, Olusubomi Olubeko |
X Demographics
The data shown below were collected from the profiles of 3 X users who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United Kingdom | 1 | 33% |
| Switzerland | 1 | 33% |
| Unknown | 1 | 33% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 3 | 100% |
Mendeley readers
The data shown below were compiled from readership statistics for 172 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 172 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 18 | 10% |
| Student > Master | 16 | 9% |
| Researcher | 14 | 8% |
| Unspecified | 10 | 6% |
| Student > Bachelor | 9 | 5% |
| Other | 24 | 14% |
| Unknown | 81 | 47% |
| Readers by discipline | Count | As % |
|---|---|---|
| Computer Science | 16 | 9% |
| Medicine and Dentistry | 13 | 8% |
| Engineering | 12 | 7% |
| Unspecified | 10 | 6% |
| Business, Management and Accounting | 6 | 3% |
| Other | 25 | 15% |
| Unknown | 90 | 52% |