Alzheimer’s Disease Diagnosis using Deep Neural Network: Review

Alzheimer’s disease is a neurological condition that is both chronic and irreversible, and there is currently no effective therapy for it. The symptoms are very modest initially, but they progressively worsen with time. If the patient and his family get an early diagnosis, they will have the chance to make choices about the future, which may include preparing for long-term care and legal and financial matters. Therefore, being able to accurately predict the progression of Alzheimer’s disease is essential for both clinical treatment and medical research. The diagnosis of Alzheimer’s disease is becoming ever more accurate as more aspects of healthcare are digitized. Several further strategies using machine learning have been proposed. Now, in the present day, deep learning has shown promising results in diagnosing Alzheimer’s disease. Various deep networks exist, such as the Convolutional Neural Network (CNN), which has 2D and 3D capabilities. Therefore, the authors of this publication would be interested in researching other works in this sector that may be used in conjunction with magnetic resonance imaging (MRI) to identify this illness. These works, together with their comparisons and discussions, will be presented.