Table 3 Performance measures for developed machine learning algorithms for the detection of SSIs

0.421 (0.214–0.605)

0.836 (0.687–0.984)

0.224 (0.114–0.334)

72.73 (39.03–93.98)

94.41 (91.41–96.60)

29.63 (19.27–42.61)

99.07 (97.60–99.65)

0.552 (0.385–0.693)

0.868 (0.765–0.97)

0.348 (0.237–0.459)

80.00 (56.34–94.27)

93.51 (90.34–95.89)

42.11 (31.47–53.52)

98.75 (97.06–99.48)

0.699 (0.575–0.805)

0.934 (0.873–0.995)

0.527 (0.419–0.635)

93.55 (78.58–99.21)

93.24 (90.02–95.66)

55.77(45.67–65.41)

99.37 (97.65–99.84)

0.414 (0.174–0.640)

0.755 (0.587–0.923)

0.196 (0.967–0.296)

54.55 (23.38–83.25)

96.47 (93.92–98.16)

33.33 (18.73–52.03)

98.50 (97.17–99.21)

0.638 (0.439–0.794)

0.857 (0.752–0.962)

0.431 (0.307–0.554)

75.00 (50.90–91.34)

96.46 (93.90–98.16)

55.56 (40.43–69.71)

98.49 (96.84–99.29)

0.735 (0.607–0.848)

0.886 (0.808–0.963)

0.561 (0.452–0.67)

80.65 (62.53–92.55)

96.47 (93.92–98.16)

67.57 (53.80–78.85)

98.20 (96.38–99.12)

0.500 (0.222–0.714)

0.762 (0.596–0.929)

0.266 (0.142–0.39)

54.55 (23.38–83.25)

97.94 (95.80–99.17)

46.15 (25.65–68.05)

98.52 (97.21–99.22)

0.714 (0.522–0.857)

0.865 (0.762–0.968)

0.525 (0.393–0.657)

75.00 (50.90–91.34)

97.94 (95.79–99.17)

68.18 (49.66–82.31)

98.52 (96.88–99.30)

0.788 (0.667–0.896)

0.906 (0.835–0.978)

0.637 (0.528–0.746)

83.87 (66.27–94.55)

97.35 (95.03–98.78)

74.29 (59.82–84.86)

98.51 (96.74–99.33)