Neural network classification of infrared spectra of control and Alzheimer's diseased tissue

Download
  1. Get@NRC: Neural network classification of infrared spectra of control and Alzheimer's diseased tissue (Opens in a new window)
DOIResolve DOI: http://doi.org/10.1016/0933-3657(94)00027-P
AuthorSearch for: ; Search for: ; Search for: ; Search for: ; Search for: ; Search for: ; Search for:
TypeArticle
Journal titleArtificial Intelligence in Medicine
ISSN0933-3657
Volume7
Issue1
Pages6779; # of pages: 13
SubjectArtificial neural networks; IT; CNS; Discriminant analysis; Alzheimer's disease; Infrared spectroscopy
AbstractArtificial neural network classification methods were applied to infrared spectra of histopathologically confirmed Alzheimer's diseased and control brain tissue. Principal component analysis was used as a preprocessing technique for some of these artificial neural networks while others were trained using the original spectra. The leave-one-out method was used for cross-validation and linear discriminant analysis was used as a performance benchmark. In the cases where principal components were used, the artificial neural networks consistently outperformed their linear discriminant counterparts; 100% versus 98% correct classifications, respectively, for the two class problem, and 90% versus 81% for a more complex five class problem. Using the original spectra, only one of the three selected artificial neural network architectures (a variation of the back-propagation algorithm using fuzzy encoding) produced results comparable to the best corresponding principal component cases: 98% and 85% correct classifications for the two and five class problems, respectively.
Publication date
PublisherElsevier Science B.V.
LanguageEnglish
AffiliationNational Research Council Canada; NRC Institute for Biodiagnostics
Peer reviewedYes
NRC number149
NPARC number9742435
Export citationExport as RIS
Report a correctionReport a correction
Record identifiere323be31-f0f4-4ca8-9271-138c85517f2d
Record created2009-07-17
Record modified2016-11-21
Bookmark and share
  • Share this page with Facebook (Opens in a new window)
  • Share this page with Twitter (Opens in a new window)
  • Share this page with Google+ (Opens in a new window)
  • Share this page with Delicious (Opens in a new window)