Backpropogation model, C4.5 algorithm, Bayesian Network, Particle Swarm Optimization [7]. We present a performance study on these algorithms in terms of accuracy and some outstanding characteristics.

No abstract

ABSTRACT

No abstract

Coronavirus Disease 2019 (COVID-19) pandemic is leading to a Public Health Emergency of International Concern (PHEIC) across the globe. COVID-19 has been found to be associated with the dysfunction of several vital organs in addition to respiratory failure. Though biochemical findings among COVID-19 patients have been partially characterized in some case studies, published systematic reviews with consolidated biochemical findings of COVID-19 are not yet available. The role of biochemical monitoring in the screening of COVID-19 cases has not been definitely established. Hence, the significance of laboratory parameters in assessing the severity and prognosis of COVID-19 cases is discussed with a focus on various hematological, biochemical, and metabolic alterations in patients suffering from COVID-19 infection. We conclude that biochemical monitoring of COVID-19 patients helps in identifying critically ill patients even earlier, aiming to reduce mortality and improve the recovery rate.