Table 8 Comparative evaluation of the DE algorithm versus metaheuristic algorithms using the OASIS dataset

From: Automated Alzheimer’s disease detection using active learning model with reinforcement learning and scope loss function

Algorithm

Accuracy

F-measure

G-measure

AUC

FA

77.479 ± 0.093

78.846 ± 0.093

79.737 ± 0.021

0.660 ± 0.059

SSA

79.171 ± 0.018

79.706 ± 0.100

80.616 ± 0.080

0.672 ± 0.026

BA

80.555 ± 0.015

80.965 ± 0.096

81.876 ± 0.042

0.689 ± 0.069

COA

81.543 ± 0.069

82.323 ± 0.063

83.229 ± 0.012

0.703 ± 0.024

HMS

83.088 ± 0.095

83.667 ± 0.078

84.486 ± 0.032

0.714 ± 0.060

ABC

83.827 ± 0.087

84.536 ± 0.093

85.396 ± 0.075

0.731 ± 0.055

DE

85.546 ± 0.061

85.849 ± 0.087

86.664 ± 0.074

0.660 ± 0.059

Proposed DE

88.806 ± 0.051

92.044 ± 0.048

92.923 ± 0.079

0.753 ± 0.045

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