| Title |
An internet‐based algorithm for diabetic foot infection during the COVID‐19 pandemic
|
|---|---|
| Published in |
Journal of Foot and Ankle Research, June 2020
|
| DOI | 10.1186/s13047-020-00405-z |
| Pubmed ID | |
| Authors |
Chao Liu, Wen‐Li Shi, Jia‐Xing You, Hong‐Ye Li, Lin Li |
X Demographics
The data shown below were collected from the profiles of 22 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 | 6 | 27% |
| United States | 5 | 23% |
| Mexico | 2 | 9% |
| Canada | 1 | 5% |
| Unknown | 8 | 36% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 15 | 68% |
| Scientists | 4 | 18% |
| Practitioners (doctors, other healthcare professionals) | 2 | 9% |
| Science communicators (journalists, bloggers, editors) | 1 | 5% |
Mendeley readers
The data shown below were compiled from readership statistics for 103 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 103 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Master | 13 | 13% |
| Other | 11 | 11% |
| Student > Bachelor | 11 | 11% |
| Researcher | 8 | 8% |
| Professor | 5 | 5% |
| Other | 18 | 17% |
| Unknown | 37 | 36% |
| Readers by discipline | Count | As % |
|---|---|---|
| Medicine and Dentistry | 21 | 20% |
| Nursing and Health Professions | 15 | 15% |
| Psychology | 7 | 7% |
| Biochemistry, Genetics and Molecular Biology | 3 | 3% |
| Pharmacology, Toxicology and Pharmaceutical Science | 3 | 3% |
| Other | 13 | 13% |
| Unknown | 41 | 40% |