# A Novel Bayesian Optimization-Based Machine Learning Framework for COVID-19 Detection From Inpatient Facility Data

**Type:** Papers  
**Canonical URL:** https://scholariq.org/papers/a-novel-bayesian-optimization-based-machine-learning-framework-for-covid-19/

## Facts

| Field | Value |
| --- | --- |
| Author Names | Md. Abdul Awal,Mehedi Masud,Md. Shahadat Hossain,Abdullah Al-Mamun Bulbul,Saifuddin Mahmud,Anupam Kumar Bairagi |
| Citations | 86 |
| DOI | 10.1109/access.2021.3050852 |
| Fields | Computer Science,Medicine |
| Open Access | true |
| OA Status | gold |
| OA URL | https://ieeexplore.ieee.org/ielx7/6287639/9312710/09319642.pdf |
| OpenAlex ID | https://openalex.org/W3118490356 |
| PMID | 34786301 |
| Type | article |
| Year | 2021 |

## Paper authors

- [Anupam Kumar Bairagi](https://scholariq.org/researchers/anupam-kumar-bairagi/)

## Paper journal

- [IEEE Access](https://scholariq.org/journals/ieee-access/)

## 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/)
- [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.