**5. Conclusions**

Scientists are looking at every possible cure for the virus, and modern technology increasingly searches for a possible cure. It is pertinent that technology has become part of our everyday lives; it has additionally now been used in the fight against the coronavirus. This paper highlights the problem of the coronavirus and discusses some algorithms that are practically used in hospitals. The paper also discusses the fact that there is an interest in building a yardstick framework to examine the present methods. The present systems have

precise correctness in predicting COVID-19 symptoms with various types of pneumonia using X-rays scans; however, they do not have both interpretability and transparency. Therefore, we can conclude that technology has many capabilities to overcome the medical and social problems caused by the COVID-19 pandemic. Few such capabilities are advanced and adequate for demonstrating any impact. CT investigation performs a vital function in the mitigation of COVID-19. It was used at the initial detection of the COVID-19 virus, particularly in the extremely vulnerable, asymptomatic occurrences with non-positive PCR tests; CT may perform functions in the following points: triage of patients, estimation of deteriorating, estimation of good cure, and problem handle. The triage of patients can be divided into three categories: possibly with COVID-19, without COVID-19, and seriousness of the infection.

**Author Contributions:** Conceptualization, K.H.A. and A.M.H.; methodology, L.A., A.M.H. and S.K.M.A.; investigation, E.H.M. and B.O.G.; resources, K.H.A. and A.M.H.; writing—original draft preparation, A.M.H. and S.K.M.A.; writing—review and editing, A.M.H.; project administration, K.H.A.; funding acquisition, K.H.A.; writing—review and editing A.H.G. All authors have read and agreed to the published version of the manuscript.

**Funding:** This research was funded by the Deanship of Scientific Research at Umm Al-Qura University (https://uqu.edu.sa) for supporting this work by gran<sup>t</sup> code: (22UQU4320277DS15) to KA. The authors would like to thank the Deanship of Scientific Research at Umm Al-Qura University for supporting this work.

**Institutional Review Board Statement:** Not applicable.

**Informed Consent Statement:** Not applicable.

**Data Availability Statement:** Not applicable.

**Conflicts of Interest:** The authors declare no conflict of interest.
