Predicting Leukemia Diseases using Co-Kriging Technique

Section: Research Article
Issue
Vol. 35 No. 4 (2026): Volume 35, Issue 4
Pages
25-39

Abstract

This research paper addresses the issue of predicting leukemia types using the co-kriging technique. The study aims to identify factors influencing leukemia risk, determine the age-standardized overall incidence rate, and monitor any temporal increase in incidence rates among patients by applying a cross-variogram function based on primary variables of leukemia types and a secondary (auxiliary) variable, namely lymphadenopathy, which plays a role in leukemia pathogenesis. The data adopted in this research from real spatial data was collected in Mosul city, Iraq. The study sample included real data from the medical records of Mosul Nuclear Hospital during 2020, namely: age, sex, leukemia type, clinical symptoms, and lymphadenopathy (a marker of cancer). The study included the three most common types of leukemia: acute lymphoblastic leukemia (ALL), acute myeloid leukemia (AML), and chronic myeloid leukemia (CML). Varying prevalence rates were recorded for the different leukemia types. By cross validation in the combined spatial prediction and Error validity criteria and Error validity criteria, small values ​​were obtained that support the prediction process. It was found that the cancer incidence rate is higher in the cities than in the neighborhoods and villages of Mosul due to population density and numerous sources of pollution, in addition to radioactive contaminants resulting from military operations during the wars. Acute lymphoblastic leukemia (ALL) is classified as the most dangerous type of leukemia due to its unique biological characteristics, which make it highly aggressive and prone to rapid spread. Lymphadenopathy is a symptom of (ALL), in addition to genetic predisposition.

Keywords:

Co-kriging, Leukemia types, Cross-variogram, Error validity criteria

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Authors

Diana Ali Hussain Al-Sharabi

Department of Mathematics, College of Education for Pure Science, University of Mosul, Mosul, Iraq

Ghanim Mahmood Dhaher

Department of Mathematics, College of Education for Pure Science, University of Mosul, Mosul, Iraq

Identifiers

DOI: 10.33899/jes.v35i4.61650

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[1]
“Predicting Leukemia Diseases using Co-Kriging Technique”, JES, vol. 35, no. 4, pp. 25–39, Oct. 2026, doi: 10.33899/jes.v35i4.61650.
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How to Cite

[1]
“Predicting Leukemia Diseases using Co-Kriging Technique”, JES, vol. 35, no. 4, pp. 25–39, Oct. 2026, doi: 10.33899/jes.v35i4.61650.