Leukemia Diagnosis Made Easy: A Machine Learning Solution Using Blood Smear Images

The early identification and diagnosis of leukemia poses a significant challenge in the field of disease diagnosis, as it involves accurately distinguishing malignant leukocytes at a low cost during the initial stages of the illness. Due to the limited availability of flow cytometry equipment and the time-consuming nature of existing laboratory diagnostic methods, the diagnosis of leukemia faces challenges despite its high prevalence. Use of machine learning (ML) in disease diagnosis, this work aims to detect and classify leukemia. Utilizing ML algorithms to analyze leukemia smear images can enhance diagnostic accuracy, reduce diagnosis time, and offer faster, more affordable, and safer diagnostic services. An approach proposed involves utilizing an ML algorithm such as ANN to identify and classify the disease in patients at an early stage.