Early Detection of Alzheimer’s Disease using CNN with PSO for parameter optimization

Alzheimer’s disease (AD) is a progressive neurological disorder that causes the brain to shrink and brain cells to die. Machine learning models play an important role in early diagnosis so the patient can have an opportunity to get the treatment. This paper contains a comprehensive analysis of different machine learning methods used to detect AD. The paper proposes a model for the early detection of AD using Convolutional Neural Network (CNN) and Particle Swarm optimization (PSO) for parameter optimization. The model showed an accuracy of 94.94% which was better than the other models in comparison.