Breast cancer detection using hierarchical b-spline networks

Authors:
Yuehui Chen;Mingjun Liu;Bo Yang
Affiliations:
School of Information Science and Engineering, Jinan University, Jinan, P.R. China;School of Information Science and Engineering, Jinan University, Jinan, P.R. China;School of Information Science and Engineering, Jinan University, Jinan, P.R. China
Venue:
ICNC'06 Proceedings of the Second international conference on Advances in Natural Computation - Volume Part I
Year:
2006

Citing 1
Cited 0

Time-series forecasting using flexible neural tree model

Information Sciences: an International Journal

Quantified Score

Hi-index	0.00

Visualization

Abstract

In this paper, an optimized hierarchical B-spline network was employed to detect the breast cancel. For evolving a hierarchical B-spline network model, a tree-structure based evolutionary algorithm and the Particle Swarm Optimization (PSO) are used to find an optimal detection model. The performance of proposed method was then compared with Flexible Neural Tree (FNT), Neural Network (NN), and Wavelet Neural Network (WNN) by using the same breast cancer data set. Simulation results show that the obtained hierarchical B-spline network model has a fewer number of variables with reduced number of input features and with the high detection accuracy.