Artificial neural network prediction for cancer survival time by gene expression data

Yen Chen Chen, Wen Wen Yang, Hung Wen Chiu

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

3 Citations (Scopus)

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.

Original languageEnglish
Title of host publication3rd International Conference on Bioinformatics and Biomedical Engineering, iCBBE 2009
DOIs
Publication statusPublished - 2009
Event3rd International Conference on Bioinformatics and Biomedical Engineering, iCBBE 2009 - Beijing, China
Duration: Jun 11 2009 → Jun 13 2009

Other

Other3rd International Conference on Bioinformatics and Biomedical Engineering, iCBBE 2009
CountryChina
CityBeijing
Period6/11/09 → 6/13/09

Keywords

  • Artifical Nerual Network
  • Microarray
  • Survival time prediction

ASJC Scopus subject areas

  • Biotechnology
  • Biomedical Engineering

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    • Cite this

    Chen, Y. C., Yang, W. W., & Chiu, H. W. (2009). Artificial neural network prediction for cancer survival time by gene expression data. In 3rd International Conference on Bioinformatics and Biomedical Engineering, iCBBE 2009 [5162409] https://doi.org/10.1109/ICBBE.2009.5162409