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)