Application of artificial intelligence in chronic myeloid leukemia (CML) disease prediction and management: a sco** review

M Ram, MR Afrash, K Moulaei, M Parvin, E Esmaeeli… - BMC cancer, 2024 - Springer
Background Navigating the complexity of chronic myeloid leukemia (CML) diagnosis and
management poses significant challenges, including the need for accurate prediction of …

Machine learning and artificial intelligence in haematology

R Shouval, JA Fein, B Savani, M Mohty… - British journal of …, 2021 - Wiley Online Library
Digitalization of the medical record and integration of genomic methods into clinical practice
have resulted in an unprecedented wealth of data. Machine learning is a subdomain of …

LeuFeatx: Deep learning–based feature extractor for the diagnosis of acute leukemia from microscopic images of peripheral blood smear

P Rastogi, K Khanna, V Singh - Computers in Biology and Medicine, 2022 - Elsevier
The abnormal growth of leukocytes causes hematologic malignancies such as leukemia.
The clinical assessment methods for the diagnosis of the disease are labor-intensive and …

[HTML][HTML] Customized deep learning classifier for detection of acute lymphoblastic leukemia using blood smear images

N Sampathila, K Chadaga, N Goswami, RP Chadaga… - Healthcare, 2022 - mdpi.com
Acute lymphoblastic leukemia (ALL) is a rare type of blood cancer caused due to the
overproduction of lymphocytes by the bone marrow in the human body. It is one of the …

Method for diagnosis of acute lymphoblastic leukemia based on ViT‐CNN ensemble model

Z Jiang, Z Dong, L Wang… - Computational Intelligence …, 2021 - Wiley Online Library
Acute lymphocytic leukemia (ALL) is a deadly cancer that not only affects adults but also
accounts for about 25% of childhood cancers. Timely and accurate diagnosis of the cancer …

IoMT‐based automated detection and classification of leukemia using deep learning

N Bibi, M Sikandar, I Ud Din… - Journal of healthcare …, 2020 - Wiley Online Library
For the last few years, computer‐aided diagnosis (CAD) has been increasing rapidly.
Numerous machine learning algorithms have been developed to identify different diseases …

Automated blast cell detection for Acute Lymphoblastic Leukemia diagnosis

R Khandekar, P Shastry, S Jaishankar, O Faust… - … Signal Processing and …, 2021 - Elsevier
Abstract Acute Lymphoblastic Leukemia (ALL) is a cancer of the blood cells which is
characterized by a large number of immature lymphocytes, known as blast cells …

Automated detection and classification of leukemia on a subject-independent test dataset using deep transfer learning supported by Grad-CAM visualization

A Abhishek, RK Jha, R Sinha, K Jha - Biomedical Signal Processing and …, 2023 - Elsevier
Leukemia is a type of cancer that affects blood cells and causes fatal infection and
premature death. Modern technology enabled by the machine and advanced deep learning …

BreastNet18: a high accuracy fine-tuned VGG16 model evaluated using ablation study for diagnosing breast cancer from enhanced mammography images

S Montaha, S Azam, AKMRH Rafid, P Ghosh… - Biology, 2021 - mdpi.com
Simple Summary Breast cancer diagnosis at an early stage using mammography is
important, as it assists clinical specialists in treatment planning to increase survival rates …

A deep learning framework for leukemia cancer detection in microscopic blood samples using squeeze and excitation learning

M Bukhari, S Yasmin, S Sammad… - Mathematical …, 2022 - Wiley Online Library
Leukemia is a fatal category of cancer‐related disease that affects individuals of all ages,
including children and adults, and is a significant cause of death worldwide. Particularly, it is …