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A Neural Network Model for Estrogen Receptor Status Prediction

Iulian Nastac, Yrjö Collan, Barbro Back, Mikael Collan, Päivi Jalava, Teijo Kuopio, A Neural Network Model for Estrogen Receptor Status Prediction. TUCS Technical Reports 610, Turku Centre for Computer Science, 2004.

Abstract:

This paper reports results on using an artificial neural network (ANN) for predicting the estrogen receptor (ER) status, which is not always available, but has a place in therapy selection of breast cancer. Our results show that in more than two thirds of the cases, the ANN is able to predict the correct ER status. An optimum neural architecture was researched, and optimal cutpoint for prediction was selected on the basis of clinical data.

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BibTeX entry:

@TECHREPORT{tNaCoBaCoJaKu04a,
  title = {A Neural Network Model for Estrogen Receptor Status Prediction},
  author = {Nastac, Iulian and Collan, Yrjö and Back, Barbro and Collan, Mikael and Jalava, Päivi and Kuopio, Teijo},
  number = {610},
  series = {TUCS Technical Reports},
  publisher = {Turku Centre for Computer Science},
  year = {2004},
  keywords = {ER, neural network, training, test, prediction, cutpoint, efficiency, sensitivity, specificity},
  ISBN = {952-12-1351-5},
}

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