DocumentCode :
3756627
Title :
Applied Machine Learning to Identify Alzheimer´s Disease through the Analysis of Magnetic Resonance Imaging
Author :
Elva Mar?a ;H?ctor Gabriel ; Fern?ndez-Ruiz; Cruz-Ram?rez
Author_Institution :
Univ. Veracruzana, Xalapa, Mexico
fYear :
2015
Firstpage :
577
Lastpage :
582
Abstract :
Alzheimer´s disease is among the most common neurodegenerative diseases [1], doubling the number of patients every 5-year interval beyond age 65 [2]. Different investigations have proven that patients with Alzheimer´s disease, show volume reduction at specific areas of the brain [1, 3-11]. Some of these areas, like the precuneus, start showing atrophy since early stages of the disease [1, 3, 6, 12-14], as measured through the use of Magnetic Resonance Imaging [9]. Considering this, we studied the possible use of the precuneus as a biomarker to identify such disease. Our results suggest that the precuneus is a potential biomarker to detect Alzheimer´s disease, since 7 out of 10 patients (73.33% of accuracy) can be correctly classified.
Keywords :
"Scientific computing","Computational intelligence"
Publisher :
ieee
Conference_Titel :
Computational Science and Computational Intelligence (CSCI), 2015 International Conference on
Type :
conf
DOI :
10.1109/CSCI.2015.143
Filename :
7424158
Link To Document :
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