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X Demographics
Mendeley readers
| Title |
Data and model bias in artificial intelligence for healthcare applications in New Zealand
|
|---|---|
| Published in |
Frontiers in Computer Science, December 2022
|
| DOI | 10.3389/fcomp.2022.1070493 |
| Authors |
Vithya Yogarajan, Gillian Dobbie, Sharon Leitch, Te Taka Keegan, Joshua Bensemann, Michael Witbrock, Varsha Asrani, David Reith |
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 % |
|---|---|---|
| New Zealand | 2 | 67% |
| Switzerland | 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 33 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 33 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 5 | 15% |
| Researcher | 3 | 9% |
| Student > Master | 3 | 9% |
| Student > Bachelor | 2 | 6% |
| Unspecified | 2 | 6% |
| Other | 1 | 3% |
| Unknown | 17 | 52% |
| Readers by discipline | Count | As % |
|---|---|---|
| Computer Science | 3 | 9% |
| Engineering | 3 | 9% |
| Unspecified | 2 | 6% |
| Economics, Econometrics and Finance | 2 | 6% |
| Business, Management and Accounting | 1 | 3% |
| Other | 3 | 9% |
| Unknown | 19 | 58% |