Feature Selection Based on Mud Ring Algorithm for Improving Survival Prediction of Children Undergoing Hematopoietic Stem-Cell Transplantation

Lamiaa M. El Bakrawy, Nadjem Bailek (), Laith Abualigah, Shabana Urooj () and Abeer S. Desuky
Additional contact information
Lamiaa M. El Bakrawy: Department of Mathematics, Faculty of Science, Al-Azhar University, Cairo 11754, Egypt
Nadjem Bailek: Sustainable Development and Computer Science Laboratory, Faculty of Sciences and Technology, Ahmed Draia University of Adrar, Adrar 01000, Algeria
Laith Abualigah: Hourani Center for Applied Scientific Research, Al-Ahliyya Amman University, Amman 19328, Jordan
Shabana Urooj: Department of Electrical Engineering, College of Engineering, Princess Nourah bint Abdulrahman University, P.O. Box 84428, Riyadh 11671, Saudi Arabia
Abeer S. Desuky: Department of Mathematics, Faculty of Science, Al-Azhar University, Cairo 11754, Egypt

Mathematics, 2022, vol. 10, issue 22, 1-19

Abstract: The survival prediction of children undergoing hematopoietic stem-cell transplantation is essential for successful transplantation. However, the performance of current algorithms for predicting mortality in this patient group has not improved over recent decades. This paper proposes a new feature selection technique for survival prediction problems using the Mud Ring Algorithm (MRA). Experiments and tests were initially performed on 13 real datasets with varying occurrences to compare the suggested algorithm with other algorithms. After that, the constructed model classification performance was compared to other techniques using the bone marrow transplant children’s dataset. Modern techniques were used to acquire their classification results, which were then compared to the suggested outcomes using a variety of well-known metrics, graphical tools, and diagnostic analysis. This investigation has demonstrated that our suggested approach is comparable and outperformed other methods in terms of results. In addition, the results showed that the constructed model enhanced prediction accuracy by up to 82.6% for test cases.

Keywords: hematopoietic stem-cell transplantation; children; Mud Ring Algorithm; feature selection; artificial intelligence (search for similar items in EconPapers)
JEL-codes: C (search for similar items in EconPapers)
Date: 2022
References: View references in EconPapers View complete reference list from CitEc
Citations:

Downloads: (external link)
https://www.mdpi.com/2227-7390/10/22/4197/pdf (application/pdf)
https://www.mdpi.com/2227-7390/10/22/4197/ (text/html)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:gam:jmathe:v:10:y:2022:i:22:p:4197-:d:968069

Access Statistics for this article

Mathematics is currently edited by Ms. Emma He

More articles in Mathematics from MDPI
Bibliographic data for series maintained by MDPI Indexing Manager ().