[The current applicating state of neural network-based electroencephalogram diagnosis of Alzheimer's disease].

The structural properties of neural network models such as recurrent neural networks, convolutional neural networks and deep belief networks and their performance in the diagnosis of Alzheimer's disease are compared and analysed to provide a valuable reference for the clinical application of neural networks in the EEG diagnosis of dementia.