A Review of COVID-19 Diagnostic Methods
| Author | Reyhaneh Yaghobzadeh | en |
| Author | Seyyed Reza Kamel | en |
| Author | Koresh Shirazi | en |
| Orcid | Reyhaneh Yaghobzadeh [0000-0003-2469-0205] | en |
| Issued Date | 2019-12-31 | en |
| Abstract | The new coronavirus disease 2019 (COVID-19) has recently emerged as an acute respiratory syndrome. The virus has spread throughout the world since the primary outbreak of the disease reported in Wuhan, China. The pandemic has led to increased mortality as the most important threat of the disease in specific populations across the world. Furthermore, COVID-19 has caused significant economic problems in several countries. The early diagnosis of COVID-19 is currently an important concern for physicians and communities. The present study aimed to review the published articles regarding the diagnosis of COVID-19 until the end of February 2020. According to the results we show that deep learning and machine learning algorithms can be effectively used to the scope of the disease. | en |
| DOI | https://doi.org/10.5812/jamm.106802 | en |
| Keyword | COVID-19 | en |
| Keyword | Coronavirus Disease | en |
| Keyword | Deep Learning | en |
| Keyword | Machine Learning | en |
| Keyword | Diagnosis | en |
| Publisher | Brieflands | en |
| Title | A Review of COVID-19 Diagnostic Methods | en |
| Type | Review Article | en |
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