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X Demographics
Mendeley readers
| Title |
Predicting severe chronic obstructive pulmonary disease exacerbations using quantitative CT: a retrospective model development and external validation study
|
|---|---|
| Published in |
The Lancet Digital Health, February 2023
|
| DOI | 10.1016/s2589-7500(22)00232-1 |
| Pubmed ID | |
| Authors |
Muhammad F A Chaudhary, Eric A Hoffman, Junfeng Guo, Alejandro P Comellas, John D Newell, Prashant Nagpal, Spyridon Fortis, Gary E Christensen, Sarah E Gerard, Yue Pan, Di Wang, Fereidoun Abtin, Igor Z Barjaktarevic, R Graham Barr, Surya P Bhatt, Sandeep Bodduluri, Christopher B Cooper, Lisa Gravens-Mueller, MeiLan K Han, Ella A Kazerooni, Fernando J Martinez, Martha G Menchaca, Victor E Ortega, Robert Paine, Joyce D Schroeder, Prescott G Woodruff, Joseph M Reinhardt |
X Demographics
The data shown below were collected from the profiles of 15 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 | 4 | 27% |
| United Kingdom | 3 | 20% |
| France | 1 | 7% |
| Canada | 1 | 7% |
| Spain | 1 | 7% |
| Unknown | 5 | 33% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 8 | 53% |
| Scientists | 3 | 20% |
| Practitioners (doctors, other healthcare professionals) | 3 | 20% |
| Science communicators (journalists, bloggers, editors) | 1 | 7% |
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 | 3 | 9% |
| Unspecified | 2 | 6% |
| Professor | 2 | 6% |
| Student > Bachelor | 2 | 6% |
| Lecturer | 2 | 6% |
| Other | 6 | 18% |
| Unknown | 16 | 48% |
| Readers by discipline | Count | As % |
|---|---|---|
| Medicine and Dentistry | 7 | 21% |
| Unspecified | 2 | 6% |
| Engineering | 2 | 6% |
| Computer Science | 2 | 6% |
| Physics and Astronomy | 2 | 6% |
| Other | 2 | 6% |
| Unknown | 16 | 48% |