Ensemble Classifiers for Acute Leukemia Classification Using Microarray Gene Expression Data under uncertainty

Authors

  • Mona Gamal Faculty of Computers and Informatics, Zagazig University, Egypt
  • Abdel Nasser H Vice Dean for students' affairs, Faculty of Computer Science, MIU, Egypt
  • Ehab Rushdy Faculty of Computers and Informatics, Zagazig University, Egypt

Keywords:

AHP, TOPSIS, VIKOR, Acute Leukemia, Neutrosophic, MCDM

Abstract

One of the most prevalent cancers in children and adults, acute leukemia has the potential to lead to death if left untreated. Within a few weeks after diagnosis, childhood ALL has spread throughout the body, posing a serious health risk to the patient. Evaluation of acute leukemia contains uncertainty and incomplete information. Due to the subjective nature of the expectations, this rating procedure incorporates ambiguity and inaccuracy. To illustrate the ambiguity of our subjective judgments, we can use the triplet T, F, and I, truth, falsity, and indeterminacy (I). Therefore, a Single-Valued Neutrosophic Sets (SVNSs) approach based on AHP, TOPSIS, and VIKOR is designed and implemented in this article. Neutrosophic AHP is used to determine the weighting of criteria in this methodology. A neutrosophic TOPSIS and VIKOR model are used to rank alternatives. There is further validation and verification of the proposed methodology in the application. To demonstrate the adaptability of the offered decisions under various circumstances, sensitivity assessments and comparative analyses were carried out.

Downloads

Download data is not yet available.

Downloads

Published

2022-04-01

Issue

Section

SI#1,2024: Neutrosophical Advancements And Their Impact on Research

How to Cite

Gamal, M. ., Nasser H, A. ., & Rushdy, E. . (2022). Ensemble Classifiers for Acute Leukemia Classification Using Microarray Gene Expression Data under uncertainty. Neutrosophic Sets and Systems, 49, 164-183. https://fs.unm.edu/nss8/index.php/111/article/view/2476