A systematic review on recent advancements in deep and machine learning based detection and classification of acute lymphoblastic leukemia
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 …
required in healthcare centers. It has a significant role in early diagnosis and treatment …
A review on traditional machine learning and deep learning models for WBCs classification in blood smear images
In computer vision, traditional machine learning (TML) and deep learning (DL) methods
have significantly contributed to the advancements of medical image analysis (MIA) by …
have significantly contributed to the advancements of medical image analysis (MIA) by …
An efficient multi-level convolutional neural network approach for white blood cells classification
The evaluation of white blood cells is essential to assess the quality of the human immune
system; however, the assessment of the blood smear depends on the pathologist's …
system; however, the assessment of the blood smear depends on the pathologist's …
Classification of white blood cells using weighted optimized deformable convolutional neural networks
X Yao, K Sun, X Bu, C Zhao, Y Jin - Artificial Cells, Nanomedicine …, 2021 - Taylor & Francis
Background Machine learning (ML) algorithms have been widely used in the classification of
white blood cells (WBCs). However, the performance of ML algorithms still needs to be …
white blood cells (WBCs). However, the performance of ML algorithms still needs to be …
Hybrid inception v3 XGBoost model for acute lymphoblastic leukemia classification
S Ramaneswaran, K Srinivasan… - … Methods in Medicine, 2021 - Wiley Online Library
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 …
accounts for 25% of all pediatric cancers. It is a life‐threatening disease which if left …
Deep learning in medical hyperspectral images: A review
With the continuous progress of development, deep learning has made good progress in the
analysis and recognition of images, which has also triggered some researchers to explore …
analysis and recognition of images, which has also triggered some researchers to explore …
New segmentation and feature extraction algorithm for classification of white blood cells in peripheral smear images
This article addresses a new method for the classification of white blood cells (WBCs) using
image processing techniques and machine learning methods. The proposed method …
image processing techniques and machine learning methods. The proposed method …
[Retracted] Explainable AI in Diagnosing and Anticipating Leukemia Using Transfer Learning Method
WH Abir, MF Uddin, FR Khanam, T Tazin… - Computational …, 2022 - Wiley Online Library
White blood cells (WBCs) are blood cells that fight infections and diseases as a part of the
immune system. They are also known as “defender cells.” But the imbalance in the number …
immune system. They are also known as “defender cells.” But the imbalance in the number …
Machine learning in haematological malignancies
Machine learning is a branch of computer science and statistics that generates predictive or
descriptive models by learning from training data rather than by being rigidly programmed. It …
descriptive models by learning from training data rather than by being rigidly programmed. It …
Feature extraction of white blood cells using CMYK-moment localization and deep learning in acute myeloid leukemia blood smear microscopic images
Artificial intelligence has revolutionized medical diagnosis, particularly for cancers. Acute
myeloid leukemia (AML) diagnosis is a tedious protocol that is prone to human and machine …
myeloid leukemia (AML) diagnosis is a tedious protocol that is prone to human and machine …