Survival of patients having hepatocellular carcinoma (HCC)

Hepatocellular carcinoma (HCC) survival prediction and clinical factor ranking through computational intelligence

Dataset

HCC Survival dataset on the University of California Irvine Machine Learning Repository: https://archive.ics.uci.edu/ml/datasets/HCC+Survival

Requirements

Software: R platform with packages: easypackages, randomForest, caret, mltools, MLmetrics

Operating systems: any Linux, any Microsoft Windows, any Mac operating system running R.

Execution

To analyze the dataset for survival prediction and for feature ranking, clone/download this GitHub repository, and visit the CODE_SUBMISSION folder. For the survival prediction, type on the shell termal console:

Rscript binary_classification_v1a.r

For the feature ranking, type on the shell termal console:

Rscript feature_ranking_v1b.r

The program will print the results into files that you will find in the RIS folder.

Article

Additional information about this project is available in the following peer-reviewed published article:

Davide Chicco, Luca Oneto. "Computational intelligence identifies alkaline phosphatase (ALP), alpha-fetoprotein (AFP), and hemoglobin levels as most predictive survival factors for hepatocellular carcinoma". Health Informatics Journal 27(1), pages 1-26, 2021.

Contacts

For any information, please contact Davide Chicco at davidechicco(AT)davidechicco.it or Luca Oneto at luca.oneto(AT)gmail.com