Background Transfer learning (TL) with convolutional neural networks aims to improve
performances on a new task by leveraging the knowledge of similar tasks learned in …

Automatic Leukemia or blood cancer detection is a challenging job and is very much
required in healthcare centers. It has a significant role in early diagnosis and treatment …

For the last few years, computer‐aided diagnosis (CAD) has been increasing rapidly.
Numerous machine learning algorithms have been developed to identify different diseases …

Introduction. The early detection and diagnosis of leukemia, ie, the precise differentiation of
malignant leukocytes with minimum costs in the early stages of the disease, is a major …

The definitive diagnosis of acute lymphoblastic leukemia (ALL), as a highly prevalent
cancer, requires invasive, expensive, and time‐consuming diagnostic tests. ALL diagnosis …

Automated classification and morphological analysis of white blood cells has been
addressed since last four decades, but there is no optimal method which can be used as …

Leukemia is a fatal cancer and has two main types: Acute and chronic. Each type has two
more subtypes: Lymphoid and myeloid. Hence, in total, there are four subtypes of leukemia …

Background and objectives Morphological differentiation among blasts circulating in blood
in acute leukaemia is challenging. Artificial intelligence decision support systems hold …

Blood cancer has been a growing concern during the last decade and requires early
diagnosis to start proper treatment. The diagnosis process is costly and time-consuming …

Acute lymphoblastic leukemia (ALL) is the most common type of pediatric malignancy which
accounts for 25% of all pediatric cancers. It is a life‐threatening disease which if left …