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

被引：0
|
作者：
Gao S. [1 ,2 ]
Lima D. [1 ,2 ]
机构：
[1] School of Computer Science and Technology, Henan Polytechnic University, Henan, Jiaozuo
[2] Department of Electrical Engineering, Federal University of Santa Catarina, Florianópolis
来源：
International Journal of Cognitive Computing in Engineering | 2022年 / 3卷
关键词：
Alzheimer's disease; Deep learning; Diagnosis;
D O I：
10.1016/j.ijcce.2021.12.002
中图分类号：
学科分类号：
摘要：
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. © 2021
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页码：1 / 8
页数：7
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