Table 1.

Summary of laboratory testing and medical imaging-based methods for COVID-19 applications [34]

S.No	Data	Modality	Results
1	The patient’s RNA samples are collected from a throat swab and a specific enzyme is added to turn the RNA into two-stranded DNA	RT-PCR	If the patient’s both DNA results are positive, then the person is affected with COVID-19. The result ranges vary from 60–70% to 95–97%
2	Sputum sample	Molecular point-of-care	Automated type of test results produced within 30 min
3	Chest image	CT	CT-Based COVID-19 diagnosis results are better than those RT-PCR can offer (80–90%). But those of RT-PCR are on the low side of 60–70%. The problem with CT scan is the radiology person has to clean the scanners in between patients with a high risk of COVID-19
4	Chest image	X-Ray	X-Ray results are insensitive compared to those with CT scan. But compared to CT scan, X-ray machines are easier to clean
5	Chest image	Ultrasound CT	The ultrasound CT scan result is better than the X-ray image. But ultrasound requires closer contact between the physician and the patient which may increase contamination risks for the staff
6	Chest image	PET-CT	This technique takes more time to diagnose COVID-19 results compared to other methods
7	Chest image	CT	AI-based CT assessment using deep learning principles to detect COVID-19 on chest CT scans. Gozes et al. report a sensitivity of 98.2%, but an impressive specificity of 92.2% for their deep learning-based thoracic CT algorithm. But the problem is some persons are infected with pneumonia with COVID-19. Alibaba used segmentation and quantification of lung infection regions to differentiate COVID-19–based pneumonia and other pneumonia cases with an accuracy of 96%