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X Demographics
| Title |
The effect of using a large language model to respond to patient messages
|
|---|---|
| Published in |
The Lancet Digital Health, April 2024
|
| DOI | 10.1016/s2589-7500(24)00060-8 |
| Pubmed ID | |
| Authors |
Shan Chen, Marco Guevara, Shalini Moningi, Frank Hoebers, Hesham Elhalawani, Benjamin H Kann, Fallon E Chipidza, Jonathan Leeman, Hugo J W L Aerts, Timothy Miller, Guergana K Savova, Jack Gallifant, Leo A Celi, Raymond H Mak, Maryam Lustberg, Majid Afshar, Danielle S Bitterman |
X Demographics
The data shown below were collected from the profiles of 24 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 States | 13 | 54% |
| United Kingdom | 2 | 8% |
| Canada | 1 | 4% |
| Brazil | 1 | 4% |
| Unknown | 7 | 29% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 14 | 58% |
| Scientists | 7 | 29% |
| Practitioners (doctors, other healthcare professionals) | 2 | 8% |
| Science communicators (journalists, bloggers, editors) | 1 | 4% |