Asian Science Citation Index is committed to provide an authoritative, trusted and significant information by the coverage of the most important and influential journals to meet the needs of the global scientific community.  
ASCI Database
308-Lasani Town,
Sargodha Road,
Faisalabad, Pakistan
Fax: +92-41-8815544
Contact Via Web
Suggest a Journal
Journal of Engineering and Applied Sciences
Year: 2017  |  Volume: 12  |  Issue: 8 SI  |  Page No.: 8334 - 8339

Quality Analysis of Various Deep Learning Neural Network Classifiers for Alzheimer’s Disease Detection

A.J. Dinu, R. Ganesan, Felix Joseph and V. Balaji    

Abstract: Over the past decade, deep learning has become a powerful machine learning algorithm in the classification of clinical data for human conditions such as Alzheimer’s disease which can extract low-to-high-level features. Classification of clinical data for Alzheimer’s disease has always been challenging as there is no clinical test for Alzheimer’s disease. Doctors diagnose it by conducting assessments of patient’s cognitive decline. But its particularly difficult for them to identify Mild Cognitive Impairment (MCI) at an early stage when symptoms are less obvious. Also, it is difficult to predict whether MCI patients will develop Alzheimer’s disease or not. The accurate diagnosis of Alzheimer’s disease in the early stage is important in order to take preventive measures and to reduce the progression and severity before irreversible brain damages occur. This study gives the performance of different classifiers on deep learning neural network for Alzheimer’s disease detection.

Fulltext    |   Related Articles   |   Back
 
 
   
 
 
 
  Related Articles

 
 
 
 
 
 
 
 
Copyright   |   Desclaimer   |    Privacy Policy   |   Browsers   |   Accessibility