Fig 1.
Mortality in U.S. in the year 2020 due to respiratory diseases.
Table 1.
Comparison of key techniques in their literature.
Fig 2.
Proposed methodology.
Fig 3.
Before upsampling.
Fig 4.
After upsampling.
Fig 5.
Comparison between original and upsampled dataset.
Fig 6.
Feature selection process.
Fig 7.
Ensemble model architecture.
Fig 8.
The framework of Genetic algorithm for hyper-parameter optimization.
Table 2.
Algorithm for generating hyperparameter.
Table 3.
Dataset description.
Table 4.
Results of machine learning algorithm.
Fig 9.
Best three classifier confusion matrix and ROC curve.
Table 5.
Random forest with hyperparameter optimization.
Fig 10.
Best optimizer results for random forest.
Table 6.
Gradient boosting classifier results.
Fig 11.
Best optimizer result for gradient boosting classifier.
Table 7.
Adaboost classifier results.
Fig 12.
Best optimizer result for Adaboost classifier.
Table 8.
Results of Extra tree.
Fig 13.
Best optimizer result for Extra tree.
Table 9.
Results of Lightbgm.
Fig 14.
Best optimizer results of Lightbgm.
Table 10.
Results of Decision tree.
Fig 15.
Best optimizer results of Decision tree.
Table 11.
Results of KNN.
Fig 16.
Best optimizer results of KNN.
Table 12.
Results of gradient boosting classifier.
Fig 17.
Best optimizer results of gradient boosting classifier.
Fig 18.
Best optimizer results of Adaboost.
Table 13.
Results of Adaboost.
Fig 19.
Best optimizer results of Extra tree.
Table 14.
Results of Extra tree.
Table 15.
Results of Lightbgm.
Fig 20.
Best optimizer results of Lightbgm.
Table 16.
Results of Random Forest.
Fig 21.
Best optimizer results of Random Forest.
Table 17.
Results of Decision tree.
Table 18.
Results of KNN.
Fig 22.
Best optimizer results of Decision tree.
Fig 23.
Best optimizer results of KNN.
Fig 24.
Confusion matrix of ensemble model.
Table 19.
Comparison table of the proposed model.
Fig 25.
Statistical analysis of proposed model with other model.
Fig 26.
ROC comparison of machine learning algorithm.
Table 20.
Comparison of related studies in predicting COVID-19 diagnosis.
Fig 27.
SHAP analysis.
Fig 28.
SHAP analysis mean value.