# Artificial intelligence cooperation to support the global response to COVID-19

**Type:** Papers  
**Canonical URL:** https://scholariq.org/papers/artificial-intelligence-cooperation-to-support-the-global-response-to-covid-19/

## Facts

| Field | Value |
| --- | --- |
| Author Names | Miguel Luengo-Oroz,Katherine Hoffmann Pham,Joseph Aylett-Bullock,Robert B. Kirkpatrick,Alexandra Sasha Luccioni,Sasha Rubel,Cedric Wachholz,Moez Chakchouk,Phillippa Biggs,Tim Nguyen,Tina D Purnat,Mariano Bernardo |
| Citations | 134 |
| DOI | 10.1038/s42256-020-0184-3 |
| Fields | Computer Science,Medicine |
| Open Access | true |
| OA Status | bronze |
| OA URL | https://www.nature.com/articles/s42256-020-0184-3.pdf |
| OpenAlex ID | https://openalex.org/W3027890277 |
| Type | article |
| Year | 2020 |

## Paper authors

- [Mariano Bernardo](https://scholariq.org/researchers/mariano-bernardo/)

## Paper primary topic

- [COVID-19 diagnosis using AI](https://scholariq.org/topics/covid-19-diagnosis-using-ai/)

## Paper topics

- [COVID-19 diagnosis using AI](https://scholariq.org/topics/covid-19-diagnosis-using-ai/)
- [Artificial Intelligence in Healthcare and Education](https://scholariq.org/topics/artificial-intelligence-in-healthcare-and-education/)
- [Anomaly Detection Techniques and Applications](https://scholariq.org/topics/anomaly-detection-techniques-and-applications/)

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Source: ScholarIQ — public research metadata, principally OpenAlex. See https://scholariq.org/sources/ for provenance and https://scholariq.org/methodology/ for what these figures mean.