Research Article
COVID-19 Risk Prediction for Diabetic Patients Using Fuzzy Inference System and Machine Learning Approaches
Table 3
Rule base of the fuzzy inference.
| Sl. no. | Input parameters | Output parameter | Cough | Fever | Sore throat | Cardio. Disease | B.P. | Age | Sex | Travel history | Risk level |
| 1 | Low | Low | Low | Low | Low | Low | Low | Low | Risk level 1 | 2 | Medium | Low | Low | Low | Low | Low | Low | Low | Risk level 1 | 3 | High | Low | Low | Low | Low | Low | Low | Low | Risk level 1 | 4 | Low | Medium | Low | Low | Low | Low | Low | Low | Risk level 1 | 5 | Medium | Medium | Low | Low | Low | Low | Low | Low | Risk level 1 | 6 | High | Medium | Low | Low | Low | Low | Low | Low | Risk level 1 | 7 | Low | High | Low | Low | Low | Low | Low | Low | Risk level 1 | 8 | Medium | High | Low | Low | Low | Low | Low | Low | Risk level 1 | 9 | High | High | Low | Low | Low | Low | Low | Low | Risk level 1 | 10 | Low | Low | Medium | Low | Low | Low | Low | Low | Risk level 1 | . . . | . . . | . . . | . . . | . . . | . . . | . . . | . . . | . . . | . . . | . . . | . . . | . . . | . . . | . . . | . . . | . . . | . . . | . . . | . . . | . . . | . . . | . . . | . . . | . . . | . . . | . . . | . . . | . . . | . . . | 3888 | High | High | High | High | High | Very high | High | High | Risk level 5 |
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