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.

Keywords

• computer vision
• deep learning
• dementia prediction
• healthcare
• image style transfer
• regression analysis