Title
Artificial neural networks in the discrimination of Alzheimer's disease using biomarkers data
Abstract
This paper presents the results of a study developing artificial neural network system (ANN) for classification of Alzheimer's disease (AD) and healthy patients. The classification is done using biomarkers, from cerebrospinal fluid: albumin ratio (CSF/Serum and/or Plasma), Aβ40 (CSF), Aβ42 (CSF), tau-total (CSF) and tau-phospho (CSF). Neural network input parameters are datasets from Alzbiomarkers database. Independent t-test is used to calculate statistical difference between input parameters. Developed neural network was validated with 80 subjects from Alzbiomarkers database. Out of 45 AD subjects, 43 were correctly classified as AD patients, obtaining a sensitivity of 95.5%, and out of 35 healthy subjects 32 were correctly classified obtaining specificity of 91.43%.
Year
DOI
Venue
2016
10.1109/MECO.2016.7525762
2016 5th Mediterranean Conference on Embedded Computing (MECO)
Keywords
DocType
ISSN
Alzheimer's disease,artificial neural network,biomarker,diagnostic,classification
Conference
2377-5475
ISBN
Citations 
PageRank 
978-1-5090-2223-6
1
0.35
References 
Authors
3
3
Name
Order
Citations
PageRank
Almir Aljović110.35
Almir Badnjevic2109.40
Lejla Gurbeta330.96