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Comparison of survival function accuracy for proposed systems and other algorithms
| Author(s) | Algorithm | Accuracy (%) | Dataset |
|---|---|---|---|
| Nemati et al. [24] | IPCRidge | 49.05 |
Open-access COVID- 19 epidemiological data [25] |
| CoxPH | 70.63 | ||
| Coxnet | 70.72 | ||
| Stagewise GB | 71.47 | ||
| Componentwise GB | 70.60 | ||
| Fast SVM | 70.65 | ||
| Fast Kernel SVM | 61.05 | ||
| Proposed system |
Cox_COVID_19 (Cox regression method) |
95.71 | Novel Corona Virus 2019 Dataset-Kaggle [20] |
| Deep_Cox_COVID_19 | 100 |
Bold values indicated best results
