Prediction of death rate of breast cancer induced from average microelement absorption with neural network

Authors:
Shouju Li;Jizhe Wang;Yingxi Liu;Xiuzhen Sun
Affiliations:
State Key Laboratory of Structural Analysis for Industrial Equipment, Dalian University of Technology, Dalian, China;State Key Laboratory of Structural Analysis for Industrial Equipment, Dalian University of Technology, Dalian, China and The Second Affiliated Hospital, Dalian Medical University, Dalian, China;State Key Laboratory of Structural Analysis for Industrial Equipment, Dalian University of Technology, Dalian, China;The Second Affiliated Hospital, Dalian Medical University, Dalian, China
Venue:
LSMS'07 Proceedings of the 2007 international conference on Life System Modeling and Simulation
Year:
2007

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Abstract

Breast cancer is one of the leading causes of deaths from cancer for the female population in both developed and developing countries. The average microelement absorption can affect death rate of breast cancer. Artificial neural networks have been successfully applied to problems in the prediction of death rate of breast cancer induced from average microelement absorption. To predict the death rate of breast cancer induced from average microelement absorption using artificial neural network is feasible and a well trained artificial neural network by Levenberg-Marquardt algorithm reveals an extremely fast convergence and a high degree of accuracy. The investigation demonstrates that the proposed training and forecasting procedure is almost 100 times faster than that of classical BP algorithm and poses higher forecasting precision. With the growth of the database, more and more cases will be collected and used as training set.