X - International Journal of Information Science and Computer Mathematics (Closed Ed TRF)
Volume 1, Issue 2, Pages 137 - 146
(May 2010)
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COMPARISON OF ARTIFICIAL NEURAL NETWORK WITH REGRESSION MODELS FOR PREDICTION OF SURVIVAL AFTER SURGERY IN CANCER PATIENTS
M. L. Suresh and P. Venkatesan
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Abstract:
Cancer survival prediction in patients who had undergone surgical intervention is an important step in the decision process. The present study investigates the effects of prognostic variables on the breast cancer survival after surgery, over a period of 5-years using feed forward neural network. The neural network was trained and tested using 413 breast cancer patients for the survival prediction with 16 prognostic variables as inputs. The artificial neural network (ANN) proves to be better than regression based models in survival prediction. |
| Keywords and phrases: ANN, FFNN, CART, logistic regression, breast cancer, survival. |
| Communicated by Kewen Zhao |
| Number of Downloads: 52 | Number of Views: 283 |
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