Application of artificial neural networks in ovarian cancer early detection

Zhen Zhang, Hong Zhang, Robert C. Bast

Research output: Contribution to conferencePaperpeer-review

Abstract

The artificial neural network (ANN) classifier for discriminating malignant from benign pelvic masses was constructed based on the multilayer perceptron structure. To compensate for the small training sample size and noisy data as often occurred in medical applications, special sample selection criteria are applied to improve data quality. Preprocessing steps based on biological knowledge and data mining techniques are also taken to reduce the complexity of ANN training. The original data set was divided into two sets, one for ANN training set and the other for independent validation. Two additional independent data sets were also used for the evaluation of the system.

Original languageEnglish (US)
Pages107-112
Number of pages6
StatePublished - Jan 1 2000
Externally publishedYes
EventInternational Joint Conference on Neural Networks (IJCNN'2000) - Como, Italy
Duration: Jul 24 2000Jul 27 2000

Other

OtherInternational Joint Conference on Neural Networks (IJCNN'2000)
CityComo, Italy
Period7/24/007/27/00

ASJC Scopus subject areas

  • Software
  • Artificial Intelligence

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