Community-friendly diagnostics
Who are tests for
Bibliographic Data
| ID | 19595055 |
|---|---|
| Authors | Fifa A Rahman (0000-0002-9264-7834, corresponding author), Kenly Sikwese (corresponding author) |
| Editors | Julia Robinson (0000-0003-0719-3995), Madhukar Pai (0000-0003-3667-4536) |
| Year | 2024 |
| Volume | 4 |
| Issue | 3 |
| Pages | e0002915 |
| Publication date | 2024-03-11 |
| Open Access | Yes |
| Type | ARTICLE |
| Venue | PLOS Global Public Health (JOURNAL) |
| Journal identifiers | ISSN: 2767-3375 • E-ISSN: 2767-3375 |
| Publisher | Public Library of Science (PLoS) (PUBLISHER) |
| DOI | 10.1371/journal.pgph.0002915 |
| PMID | 38466650 |
| OpenAlex | W4392640333 |
| Language | EN |
| References cited | 7 |
Biology · Data science · Environmentally Friendly · Artificial Intelligence in Healthcare and Education · Clinical Reasoning and Diagnostic Skills · Computer Science · COVID-19 diagnosis using AI · Environmental Science · Ecology
| Highly cited | No |
|---|