CART_based Approach for Discovering Emerging Patterns in Iraqi Biochemical Dataset

Authors

  • Sarah Sameer Department of Computer Science, College of Science, University of Baghdad, Baghdad, Iraq
  • Suhad Faisal Behadili Department of Computer Science, College of Science, University of Baghdad, Baghdad, Iraq
  • Mustafa S. Abd Department of Computer Science, College of Science, University of Baghdad, Baghdad, Iraq
  • Ali Salam Earthlink Company, Baghdad, Iraq

DOI:

https://doi.org/10.24996/ijs.2022.63.1.33

Keywords:

CART, Data mining, Biochemical, Iraq

Abstract

    This paper is intended to apply data mining techniques for real Iraqi biochemical dataset to discover hidden patterns within tests relationships. It is worth noting that preprocessing steps take remarkable efforts to handle this type of data, since it is pure data set with so many null values reaching a ratio of 94.8%, then it becomes 0% after achieving these steps. However, in order to apply Classification And Regression Tree (CART) algorithm, several tests were assumed as classes, because of the dataset was unlabeled. Which then enabled discovery of patterns of tests relationships, that consequently, extends its impact on patients’ health, since it will assist in determining test values by performing only relevant tests. Therefore decreases the number of tests for patients.

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Published

2022-01-30

How to Cite

Sameer, S. ., Behadili, S. F. ., Abd, M. S. ., & Salam, A. . (2022). CART_based Approach for Discovering Emerging Patterns in Iraqi Biochemical Dataset. Iraqi Journal of Science, 63(1), 353–362. https://doi.org/10.24996/ijs.2022.63.1.33

Issue

Section

Computer Science