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Table 2 Accuracy of the previous methods and the proposed method for different AD patient groups

From: Stratifying patients using fast multiple kernel learning framework: case studies of Alzheimer’s disease and cancers

Method

Classification Model Accuracy (%)

AD/NC

AD/MCI

NC/MCI

MCIc/MCInc

Chupin et al., 2009 [8]

80.51

73.48

71.94

64.21

Ahmed et al., 2015 [11]

86.40

74.51

76.29

68.72

Khedher et al., 2015 [12]

88.96

84.59

82.41

70.11

Dai et al., 2013 [9]

90.81

85.92

81.92

71.04

Suk et al., 2014 [10]

93.05

88.98

83.67

72.86

Liu et al., 2018 [13]

95.24

90.85

86.35

74.28

Proposed method (the best result among 20 runs)

96.50

91.25

87.65

78.49

Proposed method (at 90% confidence level of t-test)

95.80

90.63

86.47

77.42