AIMC Topic: Precursor Cell Lymphoblastic Leukemia-Lymphoma
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Artificial intelligence reveals the predictions of hematological indexes in children with acute leukemia.
BMC cancer
Aug 12, 2024
Childhood leukemia is a prevalent form of pediatric cancer, with acute lymphoblastic leukemia (ALL) and acute myeloid leukemia (AML) being the primary manifestations. Timely treatment has significantly enhanced survival rates for children with acute ...
An attention-based deep learning for acute lymphoblastic leukemia classification.
Scientific reports
Jul 29, 2024
The bone marrow overproduces immature cells in the malignancy known as Acute Lymphoblastic Leukemia (ALL). In the United States, about 6500 occurrences of ALL are diagnosed each year in both children and adults, comprising nearly 25% of pediatric can...
Utilizing Deep Feature Fusion for Automatic Leukemia Classification: An Internet of Medical Things-Enabled Deep Learning Framework.
Sensors (Basel, Switzerland)
Jul 8, 2024
Acute lymphoblastic leukemia, commonly referred to as ALL, is a type of cancer that can affect both the blood and the bone marrow. The process of diagnosis is a difficult one since it often calls for specialist testing, such as blood tests, bone marr...
Automatic classification and segmentation of blast cells using deep transfer learning and active contours.
International journal of laboratory hematology
May 10, 2024
INTRODUCTION: Acute lymphoblastic leukemia (ALL) presents a formidable challenge in hematological malignancies, necessitating swift and precise diagnostic techniques for effective intervention. The conventional manual microscopy of blood smears, alth...
Radiomics model and deep learning model based on T1WI image for acute lymphoblastic leukemia identification.
Clinical radiology
May 3, 2024
AIM: This study aimed to develop highly precise radiomics and deep learning models to accurately detect acute lymphoblastic leukemia (ALL) using a T1WI image.
Automatic classification of acute lymphoblastic leukemia cells and lymphocyte subtypes based on a novel convolutional neural network.
Microscopy research and technique
Mar 6, 2024
Acute lymphoblastic leukemia (ALL) is a life-threatening disease that commonly affects children and is classified into three subtypes: L1, L2, and L3. Traditionally, ALL is diagnosed through morphological analysis, involving the examination of blood ...
Cytogenetics and genomics in pediatric acute lymphoblastic leukaemia.
Best practice & research. Clinical haematology
Aug 17, 2023
The last five decades have witnessed significant improvement in diagnostics, treatment and management of children with acute lymphoblastic leukaemia (ALL). These advancements have become possible through progress in our understanding of the genetic a...
Biomedical Diagnosis of Leukemia Using a Deep Learner Classifier.
Computational intelligence and neuroscience
Aug 29, 2022
Leukemia cancer is the most common type of cancer that occurs in childhood. The most common types are acute lymphocytic leukemia (ALL) and acute myelogenous leukemia (AML) which affect children and adults, respectively. Several health issues occur du...
BO-ALLCNN: Bayesian-Based Optimized CNN for Acute Lymphoblastic Leukemia Detection in Microscopic Blood Smear Images.
Sensors (Basel, Switzerland)
Jul 24, 2022
Acute lymphoblastic leukemia (ALL) is a deadly cancer characterized by aberrant accumulation of immature lymphocytes in the blood or bone marrow. Effective treatment of ALL is strongly associated with the early diagnosis of the disease. Current pract...
ALNett: A cluster layer deep convolutional neural network for acute lymphoblastic leukemia classification.
Computers in biology and medicine
Jul 21, 2022
Acute Lymphoblastic Leukemia (ALL) is cancer in which bone marrow overproduces undeveloped lymphocytes. Over 6500 cases of ALL are diagnosed every year in the United States in both adults and children, accounting for around 25% of pediatric cancers, ...
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