EURASIP Journal on Advances in Signal Processing

Table 1 AUC performance for ADNI and SSI data across different ratio of training and testing datasets obtained by 10-fold cross-validation

From: DL-CHI: a dictionary learning-based contemporaneous health index for degenerative disease monitoring

α=0, β^∗
Data	Ratio (%)	CHI	DL-CHI
ADNI	15	0.870 ± 0.024	0.887 ± 0.021
	20	0.883 ± 0.021	0.890 ± 0.016
	35	0.889 ± 0.014	0.936 ± 0.051
	50	0.890 ± 0.031	0.940 ± 0.047
	75	0.927 ± 0.012	0.959 ± 0.036
SSI	15	0.850 ± 0.055	0.867 ± 0.039
	20	0.861 ± 0.036	0.877 ± 0.020
	35	0.871 ± 0.012	0.886 ± 0.020
	50	0.862 ± 0.015	0.892 ± 0.041
	75	0.889 ± 0.024	0.914 ± 0.027
α^∗, β=0
ADNI	15	0.780 ± 0.016	0.863 ± 0.034
	20	0.799 ± 0.054	0.873 ± 0.024
	35	0.804 ± 0.012	0.844 ± 0.034
	50	0.818 ± 0.019	0.869 ± 0.064
	75	0.855 ± 0.064	0.905 ± 0.024
SSI	15	0.829 ± 0.064	0.860 ± 0.023
	20	0.860 ± 0.021	0.879 ± 0.016
	35	0.870 ± 0.034	0.883 ± 0.034
	50	0.880 ± 0.042	0.892 ± 0.036
	75	0.883 ± 0.026	0.895 ± 0.016
α^∗, β^∗
ADNI	15	0.865 ± 0.021	0.872 ± 0.025
	20	0.871 ± 0.023	0.881 ± 0.014
	35	0.874 ± 0.032	0.890 ± 0.026
	50	0.891 ± 0.021	0.910 ± 0.041
	75	0.901 ± 0.020	0.919 ± 0.036
SSI	15	0.741 ± 0.032	0.814 ± 0.041
	20	0.758 ± 0.034	0.820 ± 0.030
	35	0.770 ± 0.013	0.831 ± 0.036
	50	0.791 ± 0.026	0.887 ± 0.015
	75	0.806 ± 0.010	0.862 ± 0.036

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