Early warning system of Alzheimer's disease based on deep learning

Abstract

In order to overcome the problem that the signal-to-noise ratio of disease image is too low in the traditional early warning system of Alzheimer's disease, which leads to the low warning accuracy, this paper proposes a new early warning system of Alzheimer's disease based on deep learning. Design the network structure of the early warning system, and design the login registration module, early warning module and personal information modification module according to the system operation requirements. In the software part, the early MRI images of Alzheimer's disease are registered, and the registration results are input into the artificial neural network of deep learning technology, and the output results are the final early warning results. The experimental results show that, compared with the traditional early warning system, the output signal-to-noise ratio and early warning accuracy of image registration are higher, which shows that the system can effectively improve the effectiveness of early warning.