Journal of Healthcare Engineering / 2017 / Article / Tab 9

Research Article

Twin SVM-Based Classification of Alzheimer’s Disease Using Complex Dual-Tree Wavelet Principal Coefficients and LDA

Table 9

Classification performance of AD from HC over ADNI data.

MethodsAccuracySensitivitySpecificity

Proposed92.65 ± 1.1893.11 ± 1.2992.19 ± 1.56
DTCWT + PCA + TSVM91.77 ± 0.8592.48 ± 0.8991.13 ± 1.31
DTCWT + PCA + LDA + Kernel SVM90.181 ± 0.9790.276 ± 1.6090.101 ± 1.23
DTCWT + PCA + Kernel SVM82.74 ± 1.2484.43 ± 1.5181.18 ± 1.85
DWT + PCA + LDA + TSVM86.75 ± 1.6989.32 ± 1.4384.23 ± 2.21
DWT + PCA + TSVM85.88 ± 1.1688.93 ± 1.6188.93 ± 2.02
DTCWT + PCA + LDA + ANN86.97 ± 1.3086.25 ± 1.7887.72 ± 3.51
DTCWT + PCA + LDA + KNN83.89 ± 0.7581.41 ± 1.3386.34 ± 1.08
DTCWT + PCA + LDA + AdaBoost (tree)84.4883.7285.26
DWT + PCA + ANN [13]80.05 ± 0.7281.538 ± 1.4178.974 ± 1.09
DWT + PCA + KNN [11]79.964 ± 1.1978.771 ± 2.3781.08 ± 1.67
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