A REVIEW OF DIFFERENT TECHNIQUES FOR DETECTING ALZHEIMER’S DISEASE USING ANN, SVM AND DEEP LEARNING

Alzheimer's is one of the most commonly found diseases in the elderly population. As per the world health organization report of 2019, more than 50 million suffer from dementia, and the most most common form of dementia is Alzheimer's disease and more than 10 million cases are reported every year. People suffering from neurodegenerative disease primarily pertain to the elderly population. For developing advanced techniques to detect Alzheimer's disease, analysis of different existing techniques is very important. This paper briefly discusses the various techniques and challenges involved for classification using Machine Learning and Deep Learning concepts such as Artificial Neural Network (ANN), Support Vector Machine(SVM), Ensemble Methods and Deep Learning (DL) and paper will also discuss biomarkers, genetic data and image modality based on CT scan, PET scan, and MRI.