A DEMONSTRATION THAT BREAST-CANCER RECURRENCE CAN BE PREDICTED BY NEURAL NETWORK ANALYSIS

被引:63
作者
RAYDIN, PM
CLARK, GM
HILSENBECK, SG
OWENS, MA
VENDELY, P
PANDIAN, MR
MCGUIRE, WL
机构
[1] UNIV TEXAS,HLTH SCI CTR,DEPT MED,DIV ONCOL,SAN ANTONIO,TX 78282
[2] NICHOLS INST REFERENCE LABS,SAN JUAN CAPISTRANO,CA 92675
关键词
NEURAL NETWORKS; BREAST CANCER; PROGNOSIS; SURVIVAL ANALYSIS; COX REGRESSION;
D O I
10.1007/BF01811963
中图分类号
R73 [肿瘤学];
学科分类号
100214 ;
摘要
Neural Network Analysis, a form of artificial intelligence, was successfully used to predict the clinical outcome of node-positive breast cancer patients. A Neural Network was trained to predict clinical outcome using prognostic information from 1008 patients. During training, the network received as input information tumor hormone receptor status, DNA index and S-phase determination by flow cytometry, tumor size, number of axillary lymph nodes involved with tumor, and age of the patient, as well as length of clinical followup, relapse status, and time of relapse. The ability of the trained Network to determine relapse probability was then validated in a separate set of 960 patients. The Neural Network was as powerful as Cox Regression Modeling in identifying breast cancer patients at high and low risk for relapse.
引用
收藏
页码:47 / 53
页数:7
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