Ensemble Learning-Based Alzheimer's Disease Classification Using Electroencephalogram Signals and Clock Drawing Test Images.

Feature extraction and selection helped identify six highly significant features from the EEG signals, which were consistent with findings from previous studies; it was reported that altered ‘functional connectivity in the gamma band’ [ 17 , 43 ] and altered ‘theta-beta power ratio’ in AD patients were observed [ 44 ].

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