Research Article
Revisiting Warfarin Dosing Using Machine Learning Techniques
Table 1
Dataset description.
| Continuous variables |
| Target international normalized ratio | Mean | 2.5 | Std. deviation | 0.1 | Minimum | 1.8 | Maximum | 3.5 |
| Body surface area | Mean | 1.94 | Std. deviation | 0.3 | Minimum | 1.2 | Maximum | 3.4 |
| Categorical variables |
| ā | Values | Frequency | Percent |
| Gender | 0 | 1822 | 43.00% | 1 | 2415 | 57.00% |
| Race | 1 | 2663 | 62.85% | 2 | 656 | 15.48% | 3 | 918 | 21.67% |
| Deep vein thrombosis and pulmonary embolism | 0 | 3846 | 90.77% | 1 | 391 | 9.23% |
| Diabetes | 0 | 3500 | 82.61% | 1 | 737 | 17.39% |
| Congestive heart failure | 0 | 3492 | 82.42% | 1 | 745 | 17.58% |
| Valve replacement | 0 | 3243 | 76.54% | 1 | 994 | 23.46% |
| Aspirin | 0 | 3199 | 75.50% | 1 | 1038 | 24.50% |
| Simvastatin | 0 | 3608 | 85.15% | 1 | 629 | 14.85% |
| Atorvastatin | 0 | 3810 | 89.92% | 1 | 427 | 10.08% |
| Fluvastatin | 0 | 4220 | 99.60% | 1 | 17 | 0.40% |
| Lovastatin | 0 | 4153 | 98.02% | 1 | 84 | 1.98% |
| Pravastatin | 0 | 4121 | 97.26% | 1 | 116 | 2.74% |
| Rosuvastatin | 0 | 4208 | 99.32% | 1 | 29 | 0.68% |
| Amiodarone | 0 | 3984 | 94.03% | 1 | 253 | 5.97% |
| Carbamazepine | 0 | 4195 | 99.01% | 1 | 42 | 0.99% |
| Phenytoin | 0 | 4197 | 99.06% | 1 | 40 | 0.94% |
| Rifampin | 0 | 4231 | 99.86% | 1 | 6 | 0.14% |
| Sulfonamide Antibiotics | 0 | 4214 | 99.46% | 1 | 23 | 0.54% |
| Macrolide antibiotics | 0 | 4225 | 99.72% | 1 | 12 | 0.28% |
| Antifungal azoles | 0 | 4210 | 99.36% | 1 | 27 | 0.64% |
| Smoker | 0 | 3733 | 88.10% | 1 | 504 | 11.90% |
| Enzyme | 0 | 4150 | 97.95% | 1 | 87 | 2.05% |
| Patient class | 0 | 2111 | 49.82% | 1 | 2126 | 50.18% |
| Age | 1 | 9 | 0.21% | 2 | 94 | 2.22% | 3 | 189 | 4.46% | 4 | 444 | 10.48% | 5 | 806 | 19.02% | 6 | 1023 | 24.14% | 7 | 1133 | 26.74% | 8 | 511 | 12.06% | 9 | 28 | 0.66% |
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