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Artificial Neural Network Prediction for Cancer Survival Time by Gene Expression Data

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Academic year: 2021

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Artificial Neural Network Prediction for Cancer

Survival Time by Gene Expression Data

邱泓文

Chen YC;Yang WW;Chiu HW

Abstract

This study aimed at training artificial neural networks (ANN) to predict survival time in cancer patients by using microarray and clinical data. We analyzed public microarrays and clinical data sets in different kinds of cancer. We selected 15-30 genes (correlation coefficient>0.4) as ANN variables to train networks. The results shows ANN can predict survival time from Microarray data gene expression and the prediction made by the proposed neural models show a good agreement with the measurements.

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