Academic Journal of Nawroz University (AJNU), Vol.12, No.3, 2023 This is an open access article distributed under the Creative Commons Attribution License Copyright ©2017. e-ISSN: 2520-789X https://doi.org/10.25007/ajnu.v12n3a1051 281 Accurate Machine Learning Algorithms Based on Detection of Leukemia Disease: A Review Revella E. A. Armya 1 , Nawzat Sadiq Ahmed 2 1 Information Technology, Akre Technical College of Informatics, Duhok Polytechnic University, Duhok, Kurdistan Region, Iraq 2 Information Technology Management, Technical College of Administration, Duhok Polytechnic University, Duhok, Kurdistan Region, Iraq Abstract Blood cell disorders are often detected in advanced stages as the number of cancer cells is much higher than the number of normal blood cells. As one of the important aspects of diagnosing leukemia and determining its progress is identifying malignant cells. This paper illustrates the discovery of leukemia and its four main types through machine learning algorithms, as it was found that Computer-Aided Diagnosis (CAD) has progressed rapidly over the past few years. To identify leukemia, multiple machines learning algorithms have been created for early detection. Leukemia is a condition synonymous with white blood cells (WBC) that affect the bone marrow and/or blood. The early, healthy, and reliable diagnosis of leukemia has a major role in treating patients and saving their lives. To define leukemia in relation to its subtypes, several methods have been developed. However, these approaches include improvements in efficiency, learning process, and performance. This research paper is explained to enhance and provide rapid and stable detection of leukemia. To facilitate real-time collaboration between patients and healthcare providers for leukemia research, early diagnosis, and treatment. Thus it can save patients and doctors time and money. While the use of machine learning algorithms has shown accurate results, it depends on the shape and size of the sample and the type of algorithm used to classify the subtypes of leukemia (leukemia). Keywords — Leukemia, Blood Cancer, Machine Learning. 1. INTRODUCTION Leukemia is a form of blood tissue cancer. The delicate inside of the body, called bone marrow, is leukemia. Leukemia. Hematopoietic stem cells compose of the bone marrow. It evolves over time into multiple blood components such as white blood cells (WBCs), platelets, and red blood cells (RBCs), which each have distinct functions. [1][2]. Cells (RBC) are responsible for the transfer of oxygen from the lungs to the tissues of the body. Though (WBC), also known as leukocytes, is responsible for combating disease and inflammation, platelets help with clotting and control bleeding [3]. The first type of leukemia consists of two categories: chronic leukemia and acute leukemia [4]. Acute leukemia is actually referred to as acute myeloid leukemia (AML) and acute lymphocytic leukemia (ALL) and is categorized as chronic myeloid leukemia (CML) and chronic lymphocytic leukemia (CLL) [5]. Figure 1: Leukemia in Human Blood and marrow [6] In American culture, leukemia is a severe issue, affecting all children and adults and even babies below the age of 12 months. The most prevalent form of cancer is pediatric leukemia, although the study on adults by the Health Organization indicates that leukemia has been one of the 15 most common cancer types [7]. An important feature that makes cancer killer is the rapid development of irregular cells that develop past their