A review of the application of deep learning in the detection of Alzheimer's disease

Alzheimer's disease (AD) is the most common chronic disease in the elderly, with a high incidence rate. In recent years, deep learning has become popular in the field of medical image and has achieved great success. It has become the preferred method of analyzing medical images, and it has also attracted a high degree of attention in AD detection. Compared with general machine learning technology, the deep model is more accurate and efficient for AD detection. This paper This paper introduces ad related biomarkers and feature extraction methods, reviews the application of deep learning methods in AD detection, analyzes and summarizes AD detection methods and models. The results show that deep learning technology shows good performance in AD detection.