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

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.