# Framework for detecting the patients affected by COVID-19 at early stages using Internet of Things along with Machine Learning approaches with improved Accuracy

**Type:** Papers  
**Canonical URL:** https://scholariq.org/papers/framework-for-detecting-the-patients-affected-by-covid-19-at-early-stages-using/

## Facts

| Field | Value |
| --- | --- |
| Author Names | T Devi.,J. Sathya Priya,N. Deepa |
| Citations | 19 |
| DOI | 10.1109/iccci54379.2022.9740972 |
| Fields | Computer Science,Medicine |
| Open Access | false |
| OA Status | closed |
| OpenAlex ID | https://openalex.org/W4221045755 |
| Type | conference-paper |
| Year | 2022 |

## Paper authors

- [T Devi.](https://scholariq.org/researchers/t-devi/)

## Paper journal

- [2022 International Conference on Computer Communication and Informatics (ICCCI)](https://scholariq.org/journals/2022-international-conference-on-computer-communication-and-informatics-iccci/)

## 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/)
- [Anomaly Detection Techniques and Applications](https://scholariq.org/topics/anomaly-detection-techniques-and-applications/)
- [Internet of Things and AI](https://scholariq.org/topics/internet-of-things-and-ai/)

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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.