# Towards clinical data-driven eligibility criteria optimization for interventional COVID-19 clinical trials

**Type:** Papers  
**Canonical URL:** https://scholariq.org/papers/towards-clinical-data-driven-eligibility-criteria-optimization-for/

## Facts

| Field | Value |
| --- | --- |
| Author Names | Jae Hyun Kim,Casey Ta,Cong Liu,Cynthia Sung,Alex Butler,Latoya A. Stewart,Lyudmila Ena,James R. Rogers,Junghwan Lee,Anna Ostropolets,Patrick Ryan,Hao Liu,Shing M. Lee,Mitchell S.V. Elkind,Chunhua Weng |
| Citations | 27 |
| DOI | 10.1093/jamia/ocaa276 |
| Fields | Computer Science,Medicine |
| Open Access | true |
| OA Status | bronze |
| OA URL | https://academic.oup.com/jamia/article-pdf/28/1/14/35885553/ocaa276.pdf |
| OpenAlex ID | https://openalex.org/W3107174963 |
| PMID | 33260201 |
| Type | article |
| Year | 2020 |

## Paper authors

- [Latoya A. Stewart](https://scholariq.org/researchers/latoya-a-stewart/)

## Paper journal

- [Journal of the American Medical Informatics Association](https://scholariq.org/journals/journal-of-the-american-medical-informatics-association/)

## Paper primary topic

- [COVID-19 Clinical Research Studies](https://scholariq.org/topics/covid-19-clinical-research-studies/)

## Paper topics

- [COVID-19 Clinical Research Studies](https://scholariq.org/topics/covid-19-clinical-research-studies/)
- [Machine Learning in Healthcare](https://scholariq.org/topics/machine-learning-in-healthcare/)
- [Sepsis Diagnosis and Treatment](https://scholariq.org/topics/sepsis-diagnosis-and-treatment/)

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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.