Accurate Machine Learning Algorithms Based on Detection of Leukemia Disease: A Review

Abstract — Blood cell disorders are often detected in advanced stages as the number of cancer cells is much higher than normal blood cells. As one important aspects diagnosing leukemia and determining its progress identifying malignant This paper illustrates discovery four main types through machine learning algorithms, it was found that Computer-Aided Diagnosis (CAD) has progressed rapidly over past few years. To identify leukemia, multiple machines algorithms have been created for early detection. Leukemia a condition synonymous with white (WBC) affect bone marrow and/or blood. The early, healthy, reliable diagnosis major role treating patients saving their lives. define relation to subtypes, several methods developed. However, these approaches include improvements efficiency, process, performance. research explained enhance provide rapid stable detection leukemia. facilitate real-time collaboration between healthcare providers research, diagnosis, treatment. Thus can save doctors time money. While use shown accurate results, depends on shape size sample type algorithm used classify subtypes (leukemia).