TABLE IV.

The comparison below shows the accuracy rates of testing datasets obtained from various machine learning algorithms to distinguish between three major categories of adult brains.

Reference	Modality	Method	AD/MCI/NC	AD+MCI/NC	AD/NC	AD/MCI	NC/MCI
Liu et al. [32]	MRI,PET	AE+SVM	-	-	87.76	-	76.92
Suk et al. [33]	MRI,PET	LLF+SAEF+SVM	-	-	95.9	-	85
Suk et al. [34]	MRI,PET	Patch+DBM	-	-	95.35	-	85.67
Suk et al. [35]	MRI,PET	SAE+SVM	-	-	85.7	64.5	70.6
Basaia et al. [38]	MRI	DNN	-	86	-	-	98
Senanayake et al. [39]	MRI	SAE	-	-	-	-	88.72
Payan et al. [40]	MRI	CNN	85.53	-	95.39	82.24	90.13
Liu et al. [43]	MRI	CNN	88.37	-	95.01	91.82	88.73
Qiu et al. [49]	MRI	MMSE+CNN	-	-		-	90.9
Lin et al. [50]	MRI	CNN	-	-	88.79	-	-
Srinivasan et al. [53]	MRI	SYMLET+SVM	-	-	89.7	-	-
Hosseini et al. [58]	MRI	CNN	89.1	90.3	97.6	95.18	90.81
Sarraf et al. [56]	fMRI	CNN	-	-	96.8	-	-
MCADNNet	fMRI	CNN	97.43	-	97.5	98.3	97.59
MCADNNet	MRI	CNN	100	-	99.9	99.7	100