A two stage decision model for breast cancer detection

Smaranda Belciug

Abstract


The use of computer technology supporting medical decision is now widespread and pervasive across a broad range of medical areas. Accordingly, computer-aided diagnosis has become an increasingly important area for intelligent computational systems. The aim of this paper is to present a two stage model containing several different neural networks: multi-layer neural perceptron (MLP), radial basis function (RBF) and Probabilistic Neural Networks (PNN), and the effectiveness of this system on a real breast cancer database, to support the medical decision process.


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