Table. 2. Comparing state-of-the-art methods.

All model apply ADNI data as input source.

Groups	WIMOAD		IntegrationLearner [72]		MOGLAM [73]
	Acc	AUC	Acc	AUC	Acc	AUC
AD vs. EMCI	0.776	0.882	0.712	0.686	0.333	0.531
AD vs. LMCI	0.862	0.946	0.698	0.743	0.450	0.495
AD vs. MCI	0.776	0.830	0.767	0.660	0.237	0.487
CN vs. AD	0.798	0.896	0.730	0.706	0.310	0.494
CN vs. EMCI	0.803	0.888	0.662	0.706	0.474	0.536
CN vs. LMCI	0.773	0.873	0.715	0.709	0.355	0.673
CN vs. MCI	0.743	0.845	0.671	0.678	0.592	0.574
CN vs. PT	0.709	0.810	0.685	0.671	0.733	0.489
EMCI vs. LMCI	0.740	0.847	0.695	0.685	0.621	0.556
Avg	0.776	0.869	0.704	0.694	0.456	0.537