Research Area:  Machine Learning
Early detection of Alzheimer disease is crucial for deploying interventions and slowing the disease progression. A lot of machine learning and deep learning algorithms have been explored in the past decade with the aim of building an automated detection for Alzheimer. Advancements in data augmentation techniques and advanced deep learning architectures have opened up new frontiers in this field, and research is moving at a rapid speed. Hence, the purpose of this survey is to provide an overview of recent research on deep learning models for Alzheimer disease diagnosis. In addition to categorizing the numerous data sources, neural network architectures, and commonly used assessment measures, we also classify implementation and reproducibility. Our objective is to assist interested researchers in keeping up with the newest developments and in reproducing earlier investigations as benchmarks. In addition, we also indicate future research directions for this topic.
Keywords:  
MRI images
Alzheimer disease diagnosis
Deep neural networks
Alzheimer disease
Deep learning
Author(s) Name:  Narotam Singh, Patteshwari.D, Neha Soni, Amita Kapoor
Journal name:  Image and Video Processing
Conferrence name:  
Publisher name:  arXiv:2209.11282
DOI:  10.48550/arXiv.2209.11282
Volume Information:  
Paper Link:   https://arxiv.org/abs/2209.11282#