The week's pick
Reseach Article
Alzheimer Disease diagnosis using Machine Learning Strategies
| International Journal of Computer Applications |
| Foundation of Computer Science (FCS), NY, USA |
| Volume 176 - Number 13 |
| Year of Publication: 2020 |
| Authors: G. Stalin Babu, Srujana Kurasakutla, Jagadeesh Palli, Maddi Gnana Deepika |
10.5120/ijca2020920042
|
G. Stalin Babu, Srujana Kurasakutla, Jagadeesh Palli, Maddi Gnana Deepika . Alzheimer Disease diagnosis using Machine Learning Strategies. International Journal of Computer Applications. 176, 13 ( Apr 2020), 23-28. DOI=10.5120/ijca2020920042
Abstract
Alzheimer Disease which is also called as Senile Dementia. In a sentence, we can conclude that the ability of an individual to function independently is a continuous deterioration in thought, behavioral and mental abilities. In our paper, Brain Imaging via magnetic resonance imaging (MRI), is used for evaluation of patients with suspected AD. We have used Tadpole Dataset which contains information of both AD and non-AD patients. Some studies have suggested that characteristics of MRI may predict the rate of decline in AD and may guide future therapy. However, clinicians and researchers will need to use machine learning techniques that can accurately predict a patient’s progress from mild cognitive impairment to dementia in order to reach that stage. The outcome of this paper will help us to detect the disease in earlier stages by finding the accuracy of machine learning algorithms and determining the attribute that helped us in giving a maximum accuracy rate.
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