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Can circulating matrix metalloproteinases be predictors of breast cancer? A neural network modeling study

  • H. Hu*
  • , S. B. Somiari
  • , J. Copper
  • , R. D. Everly
  • , C. Heckman
  • , R. Jordan
  • , R. Somiari
  • , J. Hooke
  • , C. D. Shriver
  • , M. N. Liebman
  • *Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

At Windber Research Institute we have started research programs that use artificial neural networks (ANNs) in the study of breast cancer in order to identify heterogeneous data predictors of patient disease stages. As an initial effort, we have chosen matrix metalloproteinases (MMPs) as potential biomarker predictors. MMPs have been implicated in the early and late stage development of breast cancer. However, it is unclear whether these proteins hold predictive power for breast disease diagnosis, and we are not aware of any exploratory modeling efforts that address the question. Here we report the development of ANN models employing plasma levels of these proteins for breast disease predictions.

Original languageEnglish
Title of host publicationAdvances in Natural Computation
Subtitle of host publication1st International Conference, ICNC 2005 - Proceedings
PublisherSpringer Verlag
Pages1039-1042
Number of pages4
EditionPART I
ISBN (Print)9783540283232
DOIs
StatePublished - 2005
Event1st International Conference on Natural Computation, ICNC 2005 - Changsha, China
Duration: 27 Aug 200529 Aug 2005

Publication series

NameLecture Notes in Computer Science
NumberPART I
Volume3610
ISSN (Print)0302-9743

Conference

Conference1st International Conference on Natural Computation, ICNC 2005
Country/TerritoryChina
CityChangsha
Period27/08/0529/08/05

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