Classification of types of dementia using a neural network model

D. L. Hudson, M. E. Cohen, M. Kramer, A. Szeri, Fen-Lei Chang

Research output: Chapter in Book/Report/Conference proceedingConference contribution

2 Citations (Scopus)

Abstract

Both diagnosis of dementia and differentiation among dementia caused by different disorders continue to be a challenge with the only definitive diagnosis available from autopsy results. The diagnosis relies on the combination of factors from a number of sources. Due to the number of factors involved, the problem is suitable for a neural network solution in which all parameters can be included along with a weighting factor for each that indicates its degree of relevance to the diagnosis. The Hypernet neural network developed by Cohen and Hudson is used to combine diverse parameters including measures derived from a new method for electroencephalogram (EEG) analysis.

Original languageEnglish (US)
Title of host publication20th International Conference on Computers and Their Applications 2005, CATA 2005
Pages208-213
Number of pages6
StatePublished - 2005
Externally publishedYes
Event20th International Conference on Computers and Their Applications 2005, CATA 2005 - New Orleans, LA, United States
Duration: Mar 16 2005Mar 18 2005

Other

Other20th International Conference on Computers and Their Applications 2005, CATA 2005
CountryUnited States
CityNew Orleans, LA
Period3/16/053/18/05

Fingerprint

Neural networks
Electroencephalography

Keywords

  • Biomedical engineering
  • Computer modeling
  • Knowledge discovery
  • Neural networks
  • Pattern recognition

ASJC Scopus subject areas

  • Computer Science Applications

Cite this

Hudson, D. L., Cohen, M. E., Kramer, M., Szeri, A., & Chang, F-L. (2005). Classification of types of dementia using a neural network model. In 20th International Conference on Computers and Their Applications 2005, CATA 2005 (pp. 208-213)

Classification of types of dementia using a neural network model. / Hudson, D. L.; Cohen, M. E.; Kramer, M.; Szeri, A.; Chang, Fen-Lei.

20th International Conference on Computers and Their Applications 2005, CATA 2005. 2005. p. 208-213.

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Hudson, DL, Cohen, ME, Kramer, M, Szeri, A & Chang, F-L 2005, Classification of types of dementia using a neural network model. in 20th International Conference on Computers and Their Applications 2005, CATA 2005. pp. 208-213, 20th International Conference on Computers and Their Applications 2005, CATA 2005, New Orleans, LA, United States, 3/16/05.
Hudson DL, Cohen ME, Kramer M, Szeri A, Chang F-L. Classification of types of dementia using a neural network model. In 20th International Conference on Computers and Their Applications 2005, CATA 2005. 2005. p. 208-213
Hudson, D. L. ; Cohen, M. E. ; Kramer, M. ; Szeri, A. ; Chang, Fen-Lei. / Classification of types of dementia using a neural network model. 20th International Conference on Computers and Their Applications 2005, CATA 2005. 2005. pp. 208-213
@inproceedings{ad60bd3d4c9a4d2eba23b0426e744ad0,
title = "Classification of types of dementia using a neural network model",
abstract = "Both diagnosis of dementia and differentiation among dementia caused by different disorders continue to be a challenge with the only definitive diagnosis available from autopsy results. The diagnosis relies on the combination of factors from a number of sources. Due to the number of factors involved, the problem is suitable for a neural network solution in which all parameters can be included along with a weighting factor for each that indicates its degree of relevance to the diagnosis. The Hypernet neural network developed by Cohen and Hudson is used to combine diverse parameters including measures derived from a new method for electroencephalogram (EEG) analysis.",
keywords = "Biomedical engineering, Computer modeling, Knowledge discovery, Neural networks, Pattern recognition",
author = "Hudson, {D. L.} and Cohen, {M. E.} and M. Kramer and A. Szeri and Fen-Lei Chang",
year = "2005",
language = "English (US)",
isbn = "9781618395528",
pages = "208--213",
booktitle = "20th International Conference on Computers and Their Applications 2005, CATA 2005",

}

TY - GEN

T1 - Classification of types of dementia using a neural network model

AU - Hudson, D. L.

AU - Cohen, M. E.

AU - Kramer, M.

AU - Szeri, A.

AU - Chang, Fen-Lei

PY - 2005

Y1 - 2005

N2 - Both diagnosis of dementia and differentiation among dementia caused by different disorders continue to be a challenge with the only definitive diagnosis available from autopsy results. The diagnosis relies on the combination of factors from a number of sources. Due to the number of factors involved, the problem is suitable for a neural network solution in which all parameters can be included along with a weighting factor for each that indicates its degree of relevance to the diagnosis. The Hypernet neural network developed by Cohen and Hudson is used to combine diverse parameters including measures derived from a new method for electroencephalogram (EEG) analysis.

AB - Both diagnosis of dementia and differentiation among dementia caused by different disorders continue to be a challenge with the only definitive diagnosis available from autopsy results. The diagnosis relies on the combination of factors from a number of sources. Due to the number of factors involved, the problem is suitable for a neural network solution in which all parameters can be included along with a weighting factor for each that indicates its degree of relevance to the diagnosis. The Hypernet neural network developed by Cohen and Hudson is used to combine diverse parameters including measures derived from a new method for electroencephalogram (EEG) analysis.

KW - Biomedical engineering

KW - Computer modeling

KW - Knowledge discovery

KW - Neural networks

KW - Pattern recognition

UR - http://www.scopus.com/inward/record.url?scp=84883420030&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=84883420030&partnerID=8YFLogxK

M3 - Conference contribution

SN - 9781618395528

SP - 208

EP - 213

BT - 20th International Conference on Computers and Their Applications 2005, CATA 2005

ER -