SubjectAlzheimer’s Disease Detection
Convolutional Neural Networks
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AbstractBiomedical data relevant to several diseases are generally employed to diagnose precise physiological or pathological conditions. The objective of biomedical image analysis is exact modeling by using Artificial Intelligence (AI) algorithms to diagnose different diseases. Alzheimer’s disease (AD) is one of the most widespread dementia forms influencing the elderly people. On-time diagnosis of Alzheimer’s disease is crucial to discover innovative methods for AD treatment. AI is an efficient approach for AD detection since it can be utilized as a Computer-aided decision support systems approach in medical procedures and play a critical role to detect changes in the brain images to identify AD. This chapter presents the recent studies and advances in AI used for medical image analysis and image processing in AD detection. The main focus is to have a consistent but easy and quick model for automated AD detection relied on the application of AI methods. Hence, the focus will be on AI techniques for AD detection from brain images. Moreover, some of the AI techniques, which were utilized for AD detection is overviewed. Then a simple AD detection approach using deep learning models will be presented. The results show that CNN achieved a testing accuracy of 95.70% accuracy and a validation accuracy of 99.71% for the diagnosis of AD from brain MRI scans. The chapter will be completed with a review of the current state-of-the-art, a discussion of new trends and open challenges for potential investigation.
Book titleAugmenting Neurological Disorder Prediction and Rehabilitation Using Artificial Intelligence