# Clinical Features of Emergency Department Patients from Early COVID-19 Pandemic that Predict SARS-CoV-2 Infection: Machine-learning Approach

**Type:** Papers  
**Canonical URL:** https://scholariq.org/papers/clinical-features-of-emergency-department-patients-from-early-covid-19-pandemic/

## Facts

| Field | Value |
| --- | --- |
| Author Names | Eric Chou,Chih‐Hung Wang,Yu-Lin Hsieh,Babak Namazi,Jon Wolfshohl,Toral Bhakta,Chu‐Lin Tsai,Wan‐Ching Lien,Ganesh Sankaranarayanan,Chien‐Chang Lee,Tsung‐Chien Lu |
| Citations | 11 |
| DOI | 10.5811/westjem.2020.12.49370 |
| Fields | Computer Science,Medicine |
| Open Access | true |
| OA Status | gold |
| OA URL | https://doi.org/10.5811/westjem.2020.12.49370 |
| OpenAlex ID | https://openalex.org/W3136252605 |
| PMID | 33856307 |
| Type | article |
| Year | 2021 |

## Paper authors

- [Babak Namazi](https://scholariq.org/researchers/babak-namazi/)

## 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/)
- [Machine Learning in Healthcare](https://scholariq.org/topics/machine-learning-in-healthcare/)
- [COVID-19 Clinical Research Studies](https://scholariq.org/topics/covid-19-clinical-research-studies/)

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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.