# Machine learning based predictors for COVID-19 disease severity

**Type:** Papers  
**Canonical URL:** https://scholariq.org/papers/machine-learning-based-predictors-for-covid-19-disease-severity/

## Facts

| Field | Value |
| --- | --- |
| Author Names | Dhruv Patel,Vikram Kher,Bhushan Desai,Xiaomeng Lei,Steven Cen,Neha Nanda,Ali Gholamrezanezhad,Vinay Duddalwar,Bino Varghese,Assad A. Oberai |
| Citations | 95 |
| DOI | 10.1038/s41598-021-83967-7 |
| Fields | Mathematics,Medicine |
| Open Access | true |
| OA Status | gold |
| OA URL | https://www.nature.com/articles/s41598-021-83967-7.pdf |
| OpenAlex ID | https://openalex.org/W3107766422 |
| PMID | 33633145 |
| Type | article |
| Year | 2021 |

## Paper authors

- [Dhruv Patel](https://scholariq.org/researchers/dhruv-patel/)

## Paper journal

- [Scientific Reports](https://scholariq.org/journals/scientific-reports/)

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