Survivability prediction of colon cancer patients using neural networks

Health Informatics J. 2019 Sep;25(3):878-891. doi: 10.1177/1460458217720395. Epub 2017 Sep 19.

Abstract

We utilize deep neural networks to develop prediction models for patient survival and conditional survival of colon cancer. Our models are trained and validated on data obtained from the Surveillance, Epidemiology, and End Results Program. We provide an online outcome calculator for 1, 2, and 5 years survival periods. We experimented with multiple neural network structures and found that a network with five hidden layers produces the best results for these data. Moreover, the online outcome calculator provides conditional survival of 1, 2, and 5 years after surviving the mentioned survival periods. In this article, we report an approximate 0.87 area under the receiver operating characteristic curve measurements, higher than the 0.85 reported by Stojadinovic et al.

Keywords: Epidemiology; Surveillance; and End Results; classification; colon cancer; outcome calculator.

Publication types

  • Research Support, Non-U.S. Gov't
  • Research Support, U.S. Gov't, Non-P.H.S.

MeSH terms

  • Colonic Neoplasms / classification
  • Colonic Neoplasms / mortality*
  • Humans
  • Logistic Models
  • Neural Networks, Computer*
  • Prognosis*
  • ROC Curve
  • Survival Analysis