%A Zhang,Meng %A Gong,Xuewu %A Ma,Wenhui %A Wen,Libo %A Wang,Yuejing %A Yao,Hongbo %D 2022 %J Frontiers in Public Health %C %F %G English %K artificial neural network,age-related macular degeneration,Alzheimer's disease,relevance,Correlation %Q %R 10.3389/fpubh.2022.925147 %W %L %M %P %7 %8 2022-June-30 %9 Original Research %# %! A study on the correlation between age-related macular degeneration and Alzheimer's disease %* %< %T A Study on the Correlation Between Age-Related Macular Degeneration and Alzheimer's Disease Based on the Application of Artificial Neural Network %U https://www.frontiersin.org/articles/10.3389/fpubh.2022.925147 %V 10 %0 JOURNAL ARTICLE %@ 2296-2565 %X Age-related Macular Degeneration (AMD) is a kind of irreversible vision loss or disease caused by retinal pigment epithelial cells and neuroretinal degeneration, which has become the main cause of vision loss and blindness of the elderly over 65 years old in developed countries. The main clinical manifestations are cognitive decline, mental symptoms and behavioral disorders, and the gradual decline of daily living ability. In this paper, a feature extraction method of electroencephalogram (EEG) signal based on multi-spectral image fusion of multi-brain regions is proposed based on artificial neural network (ANN). In this method, the brain is divided into several different brain regions, and the EEG signals of different brain regions are transformed into several multispectral images by combining with the multispectral image transformation method. Using Alzheimer's disease (AD) classification algorithm, the depth residual network model pre-trained in ImageNet was transferred to sMRI data set for fine adjustment, instead of training a brand-new model from scratch. The results show that the proposed method solves the problem of few available medical image samples and shortens the training time of ANN model.