Research Article
A Predictive Model to Classify Undifferentiated Fever Cases Based on Twenty-Four-Hour Continuous Tympanic Temperature Recording
Table 4
Positive and negative predictive values of quadratic support vector machine algorithm.
| Cases | Positive predictive value (%) | Negative predictive value (%) | Positive likelihood ratio | Negative likelihood ratio |
| Tuberculosis | 81.82 (67.63–90.65) | 98.41 (90.03–99.77) | 10.93 (5.07–23.54) | 0.04 (0.01–0.27) | Intracellular bacterial infections | 75.00 (54.72–88.16) | 84.21 (77.68–89.10) | 7.67 (3.09–19.03) | 0.48 (0.31–0.73) | Dengue fever | 61.54 (37.70–80.88) | 91.57 (86.31–94.92) | 8.64 (3.27–22.84) | 0.50 (0.29–0.86) | Noninfectious diseases | 63.33 (48.90–75.72) | 89.39 (81.61–94.12) | 4.65 (2.58–8.39) | 0.32 (0.17–0.61) |
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