DETECTION OF ALZHEIMER’S DISEASE AND ASSISTANCE
Abstract
As the world is experiencing population growth, the portion of older people aged 65 and above is also growing. As a result, dementia with Alzheimer’s disease is expected to increase rapidly in the next few years. Currently, healthcare systems require accurate detection of the disease for its treatment and prevention. Therefore, it has become essential to develop a framework for the detection of Alzheimer’s disease to avoid complications. To this end, a novel framework based on deep learning (DL) methods is proposed to detect Alzheimer’s disease. The raw data from MRI scans are pre-processed, before applying a deep learning approach. Another feature of our system is to assist Alzheimer’s patients and their caregivers to provide support, like guidelines on how to handle them when they go through psychological depression, anger issues, etc., and how a person should behave with an Alzheimer’s patient. Therefore, our
system will be very effective and usable for patients and their relatives as well as caregivers. It can also provide insight into the disease, different stages, causes, symptoms, and related matters.
Keywords:
ResNet, DenseNet, LSTM, Deep LearningPublished
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