This study aims to systematically review prior research on the evaluation and benchmarking
of automated acute leukaemia classification tasks. The review depends on three reliable …

Machine Learning (ML) is a rapidly emerging field that enables a plethora of innovative
approaches to solving real-world problems. It enables machines to learn without human …

In medicine, white blood cells (WBCs) play an important role in the human immune system.
The different types of WBC abnormalities are related to different diseases so that the total …

Automatic recognition and classification of leukocytes helps medical practitioners to
diagnose various blood-related diseases by analysing their percentages. Different …

Leukemia is the rapid production of abnormal white blood cells that consequently affects the
blood and damages the bone marrow. The overproduction of abnormal and immature white …

The severity of acute lymphoblastic leukemia depends on the percentages of blast cells
(abnormal white blood cells) in bone marrow or peripheral blood. The manual microscopic …

Leukemia (blood cancer) is an unusual spread of White Blood Cells or Leukocytes (WBCs)
in the bone marrow and blood. Pathologists can diagnose leukemia by looking at a person's …

Leukemia is a hematologic cancer which develops in blood tissue and triggers rapid
production of immature and abnormal-shaped White Blood Cells. Based on statistics it is …

Acute Lymphoblastic Leukemia (ALL) is a blood cell cancer characterized by numerous
immature lymphocytes. Even though automation in ALL prognosis is an essential aspect of …

Context Acute leukaemia diagnosis is a field requiring automated solutions, tools and
methods and the ability to facilitate early detection and even prediction. Many studies have …