Using Linear Discriminant Analysis to Determine the Most Important Factors Affecting the Classification of Leukemia in Sudan

(A case study of Al-Tawrah Hospital, Khartoum, during the year 2022 AD)

Abstract

Cancer is one of the most common causes of death in the countries of the world, and chronic and acute leukemia is one of the most common types of cancer in Sudan. Therefore, it was necessary to determine the factors affecting the disease, study aimed to: classification of the disease, The efficiency of the linear discriminatory function model in classifying leukemia, the study followed the descriptive analytical methodology , representing the descriptive side in finding descriptive statistics for the variables that can lead to chronic and acute leukemia, while the analytical side represented in building mathematical models and estimating their features, significance of their capabilities and accuracy of their prediction, The study  relied on preliminary data through a questionnaire, and a simple random sample of 224 people with chronic and acute leukemia was taken from inside the Khartoum Hospital for chronic, The study used the linear discriminatory function method in analyzing the data. The variables that affect the classification of chronic and acute leukemia in the characteristics of the sample are (age - profession - and educational level), while in the health and behavioral factors are: (smoking - obesity - blood disorders - kinship), and the study concluded a number of Recommendations, the most important of which are: the use of the linear discriminatory function in the process of classifying people with chronic and acute leukemia in the future and the introduction of other variables and factors that were not mentioned in the research. Applying an electronic file archiving system to save files and protect them from damage and ease of procedure, intensifying efforts in the field of combating the spread of chronic and acute leukemia through awareness programs about the risks of the disease and the need for early diagnosis and receiving the necessary treatment doses. Low-income people in different states during the period of receiving treatment in different treatment centers.