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X Demographics
Mendeley readers
| Title |
Predicting the Disease Outcome in COVID-19 Positive Patients Through Machine Learning: A Retrospective Cohort Study With Brazilian Data
|
|---|---|
| Published in |
Frontiers in Artificial Intelligence, August 2021
|
| DOI | 10.3389/frai.2021.579931 |
| Pubmed ID | |
| Authors |
Fernanda Sumika Hojo De Souza, Natália Satchiko Hojo-Souza, Edimilson Batista Dos Santos, Cristiano Maciel Da Silva, Daniel Ludovico Guidoni |
X Demographics
The data shown below were collected from the profiles of 4 X users who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Switzerland | 1 | 25% |
| Egypt | 1 | 25% |
| Unknown | 2 | 50% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 4 | 100% |
Mendeley readers
The data shown below were compiled from readership statistics for 100 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 100 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Master | 11 | 11% |
| Student > Bachelor | 11 | 11% |
| Student > Ph. D. Student | 9 | 9% |
| Researcher | 8 | 8% |
| Other | 3 | 3% |
| Other | 13 | 13% |
| Unknown | 45 | 45% |
| Readers by discipline | Count | As % |
|---|---|---|
| Medicine and Dentistry | 18 | 18% |
| Computer Science | 12 | 12% |
| Engineering | 4 | 4% |
| Agricultural and Biological Sciences | 3 | 3% |
| Biochemistry, Genetics and Molecular Biology | 2 | 2% |
| Other | 11 | 11% |
| Unknown | 50 | 50% |