Alzheimer's Disease Analysis using Explainable Artificial Intelligence (XAI)
From this article, one can understand the analysis of Alzheimer's by using XAI with the corresponding feature explanation, so that the result is much more trustable and reliable.
Abstract
Alzheimer's disease is a progressive neurologic disorder that results in causing the brain to undergo atrophy that is it results in the brain shrinking and the brain cells to die. It occurs to a person who is in their 30's to middle 60's. Around 5.8 million people in the United States of America of age 65 and more have Alzheimer's disease. It is the common cause of dementia. No treatment has been found for Alzheimer's till date. Alzheimer's not cured can result in severe loss of brain function and finally results in death. So, it is important for one to identify it in its early stage and cure it. In this project, we have attempted to identify the stages of Alzheimer using Layer wise relevance propagation method in Explainable artificial intelligence by taking image as the input. Other than LRP, some other algorithms such as vgg-16 and CNN has been used for achieving better results and a good batch accuracy. From this article, one can understand the analysis of Alzheimer's by using XAI with the corresponding feature explanation. The result is achieved with an explanation for the analysis, so that the result is much more trustable and reliable.