# Trustworthy and Intelligent COVID-19 Diagnostic IoMT Through XR and Deep-Learning-Based Clinic Data Access

**Type:** Papers  
**Canonical URL:** https://scholariq.org/papers/trustworthy-and-intelligent-covid-19-diagnostic-iomt-through-xr-and-deep/

## Facts

| Field | Value |
| --- | --- |
| Author Names | Yonghang Tai,Bixuan Gao,Qiong Li,Zhengtao Yu,Chunsheng Zhu,Victor Chang |
| Citations | 81 |
| DOI | 10.1109/jiot.2021.3055804 |
| Fields | Computer Science,Medicine |
| Open Access | true |
| OA Status | bronze |
| OA URL | https://ieeexplore.ieee.org/ielx7/6488907/9585129/09343340.pdf |
| OpenAlex ID | https://openalex.org/W3127596160 |
| PMID | 35782175 |
| Type | article |
| Year | 2021 |

## Paper authors

- [Yonghang Tai](https://scholariq.org/researchers/yonghang-tai/)

## 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/)
- [Adversarial Robustness in Machine Learning](https://scholariq.org/topics/adversarial-robustness-in-machine-learning/)
- [Artificial Intelligence in Healthcare and Education](https://scholariq.org/topics/artificial-intelligence-in-healthcare-and-education/)

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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.