# Dementia Prediction Support Model Using Regression Analysis and Image Style Transfer
###### Abstract  
It is difficult to provide information to patients because the cause of Alzheimer's disease is not accurately identified. Therefore, there are difficulties in management and prevention. However, if one can manage the basic influencing factors, one can maintain a healthy brain. Therefore, this study proposes a prediction support model for dementia based on regression analysis using an image style transfer. The proposed method collects images of factors extracted from text information about Alzheimer's disease, images of a normal brain, and images of a brain with Alzheimer's disease to provide precautions for the factors affecting Alzheimer's disease. Accordingly, it transforms the brain's style by transferring image features of the factors affecting it onto the normal brain image. The transformed results allow for discovery of the factors that affect Alzheimer's disease, compared to the brain with Alzheimer's disease, and allow the medical team or the patients themselves to prevent and manage it. In addition, performance evaluation compares the similarities in style transmission results for factors affecting it according to each stage of the dementia condition. A comparison of similarities shows that a brain with cerebral hemorrhage and the brain of an alcoholic have the highest similarities to all stages of dementia. computer vision; deep learning; dementia prediction; healthcare; image style transfer; regression analysis; support model +
Footnote †: journal: Medical  
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of the machine. MRI scanning is impossible, and the image quality deteriorates when there are medical apparatuses that react to magnets or metal foreign substances, due to the characteristic of its use of the magnetic field [5]. Thus, since continuous monitoring requires a considerable cost, it is necessary to find a way to solve the problem of cost for continuous monitoring. In addition, it is necessary to find a way to raise attention to the need for health management [6,7]. With the development of artificial intelligence technology and the development of hardware and software, studies of deep learning are actively conducted. Of them, there is image style transfer; this keeps the main form of the image, using two images, and transforms the image style by additionally applying the desired style. There are two methods of image style transfer. First, the method of learning to transfer from one domain to another domain if images are provided from two different domains. Feedforward is used when it is applied to a new image after learning the network once. However, because it learns a new network, multiple image data are needed for each domain, and it takes much time to learn that. Second, the method of using the network that is learned in advance. Each feature map is stored, which is output when the content image and style image pass through the network, and the image data are optimized, so that the feature map of the newly synthesized image data can have similar features to the feature map extracted from the content image and style image. Style transfer is possible with two images, but it takes a long operation time to optimize the images [8,9]. Consequently, it is necessary to find ways to avoid distorting the data and to reduce operation time. Thus, this study proposes a prediction support model for dementia based on regression analysis using an image style transfer. The contributions of the proposed method are as follows:  
* This is a method for collecting features and evidence needed for management, prevention, and diagnosis through an analysis of various factors that affect Alzheimer's disease and monitoring the dementia condition according to changes in the brain. The factors affecting dementia are extracted through regression analysis, and the regression coefficient is used as the degree of impact. In addition, images of the factors affecting it are extracted, and results from the regression analysis are collected.