Diagnosis and classification of Alzheimer's disease by 3 D Residual Block

In recent years, many studies have been done to analyze brain diseases in order to identify brain diseases that have a significant role in creating diagnostic intelligent systems. among the different methods of machine learning, deep learning based methods in recent years have been a wide application of the development of intelligent systems, which resulted in the creation of powerful systems for diagnosis of disease.

In this study, the diagnosis of Alzheimer's patients with deep learning neural network is based on method of 3- D Residual  Block. the training and test procedure presented by ADNI data set  

The results showed that the output of this Method were conducted in comparison to the proposed methods, accuracy of diagnose and classification of Alzheimer's disease.

the findings of the present study showed that the machine learning with deep learning methods can diagnose Alzheimer's disease sooner than doctors.