COVID-19 Severity Prediction Using Enhanced Whale with Salp Swarm Feature Classification

Computerized tomography (CT) scans and X-rays play an important role in the diagnosis of COVID-19 pneumonia. On basis image analysis results chest CT X-rays, severity lung infection is monitored using a tool. Many researchers have done accurate efficient takes lot time inefficient. To overcome these issues, our proposed study implements four cascaded stages. First, for pre-processing, mean filter used. Second, texture feature extraction uses principal component (PCA). Third, modified whale optimization algorithm used (MWOA) selection algorithm. The detected on age group. Fourth, classification by MWOA with salp swarm (MWOA-SSA). MWOA-SSA has accuracy 97%, whereas PCA accuracies 81% 86%. sensitivity rate better that than (84.4%) (95.2%). outperforms other algorithms specificity 97.8%. This method improves effective affected images from large datasets.