| Title |
Artificial Intelligence for COVID-19 Drug Discovery and Vaccine Development
|
|---|---|
| Published by |
Frontiers, August 2020
|
| DOI | 10.3389/frai.2020.00065 |
| Pubmed ID | |
| Authors |
Arash Keshavarzi Arshadi, Julia Webb, Milad Salem, Emmanuel Cruz, Stacie Calad-Thomson, Niloofar Ghadirian, Jennifer Collins, Elena Diez-Cecilia, Brendan Kelly, Hani Goodarzi, Jiann Shiun Yuan |
X Demographics
The data shown below were collected from the profiles of 192 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 | 53 | 28% |
| India | 9 | 5% |
| United Kingdom | 8 | 4% |
| Argentina | 4 | 2% |
| Taiwan | 2 | 1% |
| Peru | 2 | 1% |
| Germany | 2 | 1% |
| Mexico | 2 | 1% |
| Colombia | 1 | <1% |
| Other | 11 | 6% |
| Unknown | 98 | 51% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 159 | 83% |
| Scientists | 29 | 15% |
| Science communicators (journalists, bloggers, editors) | 3 | 2% |
| Practitioners (doctors, other healthcare professionals) | 1 | <1% |
Mendeley readers
The data shown below were compiled from readership statistics for 361 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 361 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Bachelor | 47 | 13% |
| Student > Master | 44 | 12% |
| Researcher | 40 | 11% |
| Student > Ph. D. Student | 31 | 9% |
| Student > Doctoral Student | 15 | 4% |
| Other | 36 | 10% |
| Unknown | 148 | 41% |
| Readers by discipline | Count | As % |
|---|---|---|
| Biochemistry, Genetics and Molecular Biology | 45 | 12% |
| Computer Science | 32 | 9% |
| Medicine and Dentistry | 19 | 5% |
| Engineering | 19 | 5% |
| Pharmacology, Toxicology and Pharmaceutical Science | 14 | 4% |
| Other | 72 | 20% |
| Unknown | 160 | 44% |