A Review on Alzheimer’s Disease Detection using Machine Learning

Alzheimer's disease is a progressive and irreversible brain disorder affecting millions worldwide. The timely detection of Alzheimer's Disease (AD) is essential for the effective management and treatment of the disease. Machine learning (ML) approaches have shown promising results in detecting AD at an early stage. This review article provides an overview of the recent developments in the application of ML techniques for AD detection. Also discusses the application of certain image processing, feature extraction, and ML techniques for detecting AD. The article covers various ML algorithms and their performance in detecting AD with different data sources, such as MRI, PET, etc. with their advantages and limitations. Overall, this research study demonstrates the potential of ML approaches in improving the accuracy and efficiency of Alzheimer's disease detection, which could lead to better patient outcomes and disease management.