3 Citations (Scopus)


This paper applies Classification and Regression Tree (CART) to classify the selected compounds of cancer drugs related to radiation protection for cancer treatment. CART is one of machine learning methods that has been widely applied in drug design due to its simple algorithm and efficiency. The classification is applied to the 5%, 10%, 20%, 30%, 35% most important features selected by Mean Decreasing Gini Index. Moreover, the performance of CART on classification with full features is also investigated. The analysis shows that classification of cancer drug compounds using CART reached 79% accuracy when it uses 5% or 10% most important features. In this case, the performance of CART is slightly better than other complex machine learning methods applied in the previous researches.

Original languageEnglish
Pages (from-to)458-465
Number of pages8
JournalProcedia Computer Science
Publication statusPublished - 2019
Event5th Information Systems International Conference, ISICO 2019 - Surabaya, Indonesia
Duration: 23 Jul 201924 Jul 2019


  • CART
  • Drug discovery
  • Machine learning
  • Toxicity


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