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Hepatocellular Carcinoma Survival Prediction Using Deep Neural Network

  • Chayan Kumar Kayal
  • Sougato Bagchi
  • Debraj Dhar
  • Tirtha Maitra
  • Sankhadeep Chatterjee
Conference paper
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 811)

Abstract

Hepatocellular carcinoma is one of the most common types of liver cancer in adults. In patients having this disease, prediction of survival is very strenuous. Through this eminent experiment, the authors have proposed a new improved classification approach using DNN (deep neural network) for predicting survival of patients with hepatocellular carcinoma. The dataset was obtained at a University Hospital in Portugal and contains several demographic, risk factors, laboratory and overall survival features of 165 real patients diagnosed with HCC. Authors have selected 15 risk factors out of 49 risk factors which are significantly responsible for HCC in this proposed method. The outcome of this experiment has proved to be of significant increase in accuracy of the prediction of survival over the conventional methods like multivariable Cox model or unsupervised classification.

Keywords

Hepatocellular carcinoma Classification Deep neural network Survival 

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Copyright information

© Springer Nature Singapore Pte Ltd. 2019

Authors and Affiliations

  • Chayan Kumar Kayal
    • 1
  • Sougato Bagchi
    • 1
  • Debraj Dhar
    • 1
  • Tirtha Maitra
    • 1
  • Sankhadeep Chatterjee
    • 1
  1. 1.Department of Computer Science & EngineeringUniversity of Engineering and ManagementKolkataIndia

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