Table 2 Performance comparison between the proposed method and other methods on the MOST dataset.

From: A siamese network with adaptive gated feature fusion for individual knee OA features grades prediction

Methods

Top1

knee OA/non-knee OA

KL

FL

FM

TL

TM

JSN-L

JSN-M

Antony et al., 201719

–

49.48%

–

–

–

–

–

–

Tiulpin et al., 201812

–

68.73%

–

–

–

–

–

–

Chen et al., 201939

–

75.56%

–

–

–

–

–

–

Mikhaylichenko et al., 202141

–

73.43%

–

–

–

–

–

–

SE-ResNet-5014

–

74.39%

79.32%

78.33%

76.87%

71.19%

93.20%

84.00%

SE-ResNext50-32x4d14

–

75.22%

78.98%

78.72%

78.04%

73.11%

93.43%

84.16%

Ensemble14

–

76.13%

80.31%

79.23%

78.42%

73.56%

93.69%

84.83%

Ours

92.58%

76.94%

82.05%

80.54%

80.12%

76.32%

93.54%

83.77%

Ours (Ens.)

92.84%

77.86%

80.88%

79.91%

79.52%

76.71%

93.31%

84.19%

Methods

Top±1

–

KL

FL

FM

TL

TM

JSN-L

JSN-M

Antony et al., 201719

–

73.06%

–

–

–

–

–

–

Tiulpin et al., 201812

–

90.28%

–

–

–

–

–

–

Chen et al., 201939

–

98.09%

–

–

–

–

–

–

Mikhaylichenko et al., 202141

–

95.67%

–

–

–

–

–

–

SE-ResNet-5014

–

98.26%

93.72%

92.16%

94.55%

97.73%

98.17%

98.18%

SE-ResNext50-32x4d14

–

98.20%

95.16%

93.28%

96.45%

97.84%

98.26%

98.26%

Ensemble14

–

98.43%

94.64%

93.20%

95.80%

97.97%

98.30%

98.28%

Ours

–

98.59%

95.55%

94.06%

96.87%

98.15%

98.33%

98.21%

Ours (Ens.)

–

98.12%

94.86%

93.72%

96.59%

98.10%

98.20%

98.31%