Leukemia Blood Cell Image Classification Using Machine Learning - A Systematic Literature Review

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Zemen Mawlood Mohammed
Esraa Zeki Mohammed


A rise in the quantity of young blood cells in the both blood and bone marrow is the primary cause of leukemia, a malignant condition that affects the system that produces blood. This disease appears in the elderly and represents the most common type of disease among young people. Symptoms appear in the form of bleeding, bruising, a feeling of fatigue, a high temperature, and a high rate of transmission of the disease. These symptoms occur due to a deficiency of mature and normal blood cells. The cause of this disease is unknown, as there are different causes depending on the type of leukemia. The genetic factor, weather and environmental conditions have a major and major role in the causes of the disease. Where there are factors that lead to an increase in the chances of contracting the disease, such as smoking, ionizing radiation, and some chemical elements. Also, individuals with a family history of the disease also have an increased chance of developing the disease. The disease can be detected and diagnosed with a blood test or by taking a dose of bone tissue. White blood cells are capable of divided into the following categories: neutrophils, monocytes, eosinophils, lymphocytes and basophils. During this period, the authors designed a CNN to classify and detect normal white blood cells. The following two actions are taken by the system in order to identify the type and shape of a typical white blood cell. Finding the primary traits and characteristics of typical WBCs is the first step. The classification of mature WBCs according to kind is the other duty. The device will be able to detect mature and normal WBCs using CNN by comparing their properties to those of higher level normal WBCs. With the amount of data used, the accuracy of the suggested method was up to 96.78%. The most pertinent studies showing the value of machine learning and its algorithms in detection, medical image segmentation, tagging, and classification, particularly leukemia, are presented and discussed in this paper.

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Mohammed, Z. M., & Mohammed, E. Z. (2023). Leukemia Blood Cell Image Classification Using Machine Learning - A Systematic Literature Review. Journal of Advanced Sciences and Nanotechnology, 2(2), 204–214. https://doi.org/10.55945/joasnt.2023.2.2.204-214


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