A Comparison of Decision Tree Algorithms in the Assessment of Biomedical Data.

Journal: BioMed research international
Published Date: Jul 7, 2022

Abstract

By comparing the performance of various tree algorithms, we can determine which one is most useful for analyzing biomedical data. In artificial intelligence, decision trees are a classification model known for their visual aid in making decisions. WEKA software will evaluate biological data from real patients to see how well the decision tree classification algorithm performs. Another goal of this comparison is to assess whether or not decision trees can serve as an effective tool for medical diagnosis in general. In doing so, we will be able to see which algorithms are the most efficient and appropriate to use when delving into this data and arrive at an informed decision.

Authors

  • Fahima Hajjej
    Department of Information Systems, College of Computer and Information Sciences, Princess Nourah bint Abdulrahman University, Riyadh, Saudi Arabia.
  • Manal Abdullah Alohali
    Department of Information Systems, College of Computer and Information Sciences, Princess Nourah bint Abdulrahman University, P.O. Box 84428, Riyadh 11671, Saudi Arabia.
  • Malek Badr
    The University of Mashreq, Research Center, Baghdad, Iraq.
  • Md Adnan Rahman
    Green Business School, Green University of Bangladesh, Bangladesh.

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