Table 1. Comparison with state-of-the-art methods.

Author	Processing and training	Classification	Modalities	Accuracy (Eq:7)	Sensitivity (Eq:5)	Specificity (Eq:6)
Basaia et al. (2019) [30]	Whole Brain	CNN	AD-NC,AD-MCI,MCI-CN	99.21)75.487.187.7	98.974.587.7	99.576.474.6
Wang et al. (2021) [31]	Hippocampus-based biomarker	Dense CNN	AD-NC	89.8	98.5	85.2
Liu et al. (2019) [16]	Segmented hippocampus	Multi-model CNN	AD-NC	88.9	86.6	90.8
Katabathua et al. (2021) [15]	Hippocampus atrophy	DenseCNN2	AD-NC	92.5	88.2	94.9
Zhang et al. (2021) [32]	Whole brain	CAM-CNN	AD-NC	97.3	97.1	99.7
Proposed method	Hippocampus atrophy	Efficient Net	AD-NC	962)	96.9	100

Best accuracy in whole brain AD classification.
Best accuracy in hippocampus atrophy AD classification.