On the use of artificial neural networks for the analysis of survival data

被引：35

作者：

Brown, SF ^{[1
]}

Branford, AJ ^{[1
]}

Moran, W ^{[1
]}

机构：

[1] COOPERAT RES CTR SENSOR SIGNAL & INFORMAT PROC,ADELAIDE,SA 5001,AUSTRALIA

来源：

IEEE TRANSACTIONS ON NEURAL NETWORKS | 1997年 / 8卷 / 05期

关键词：

backpropagation; neural-network applications; statistics; survival analysis;

D O I：

10.1109/72.623209

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

Artificial neural networks are a powerful tool for analyzing data sets where there are complicated nonlinear interactions between the measured inputs and the quantity to be predicted. We show that the results obtained when neural networks are applied to survival data depend critically on the treatment of censoring in the data. When the censoring is modeled correctly, neural networks are a robust model independent technique for the analysis of very large sets of survival data.

引用

页码：1071 / 1077

页数：7

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