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 …
[HTML][HTML] A review of artificial intelligence applications in hematology management: current practices and future prospects
Background Machine learning (ML) and deep learning (DL) methods have recently
garnered a great deal of attention in the field of cancer research by making a noticeable …
garnered a great deal of attention in the field of cancer research by making a noticeable …
[HTML][HTML] The impact of artificial intelligence on health equity in oncology: scoping review
Background The field of oncology is at the forefront of advances in artificial intelligence (AI)
in health care, providing an opportunity to examine the early integration of these …
in health care, providing an opportunity to examine the early integration of these …
Multi-method diagnosis of blood microscopic sample for early detection of acute lymphoblastic leukemia based on deep learning and hybrid techniques
Leukemia is one of the most dangerous types of malignancies affecting the bone marrow or
blood in all age groups, both in children and adults. The most dangerous and deadly type of …
blood in all age groups, both in children and adults. The most dangerous and deadly type of …
Acute lymphoblastic leukemia detection from microscopic images using weighted ensemble of convolutional neural networks
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 …
immature lymphocytes. Even though automation in ALL prognosis is an essential aspect of …
[HTML][HTML] Ensemble of convolutional neural networks to diagnose acute lymphoblastic leukemia from microscopic images
Abstract Acute Lymphoblastic Leukemia (ALL) is a blood cell cancer characterized by the
presence of excess immature lymphocytes., Even though automation in ALL prognosis is …
presence of excess immature lymphocytes., Even though automation in ALL prognosis is …
Gaussian blurring technique for detecting and classifying acute lymphoblastic leukemia cancer cells from microscopic biopsy images
TG Devi, N Patil, S Rai, CS Philipose - Life, 2023 - mdpi.com
Visual inspection of peripheral blood samples is a critical step in the leukemia diagnostic
process. Automated solutions based on artificial vision approaches can accelerate this …
process. Automated solutions based on artificial vision approaches can accelerate this …
Symptom based explainable artificial intelligence model for leukemia detection
Leukemia is not only fatal in nature, it is also extremely expensive to treat. However,
leukemia detection at early stage can save lives and money of the affected people, specially …
leukemia detection at early stage can save lives and money of the affected people, specially …
Uncertainty quantification for MLP-mixer using Bayesian deep learning
Convolutional neural networks (CNNs) have become a popular choice for various image
classification applications. However, the multi-layer perceptron mixer (MLP-Mixer) …
classification applications. However, the multi-layer perceptron mixer (MLP-Mixer) …
Effective dimensionality reduction model with machine learning classification for microarray gene expression data
YK Saheed - Data Science for Genomics, 2023 - Elsevier
Microarray technology enables biologists to simultaneously monitor the activities of genome-
wide features. This method generates gene expression data that can be used to classify …
wide features. This method generates gene expression data that can be used to classify …