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OpenAlex is a bibliographic catalogue of scientific papers, authors and institutions accessible in open access mode, named after the Library of Alexandria. It's citation coverage is excellent and I hope you will find utility in this listing of citing articles!

If you click the article title, you'll navigate to the article, as listed in CrossRef. If you click the Open Access links, you'll navigate to the "best Open Access location". Clicking the citation count will open this listing for that article. Lastly at the bottom of the page, you'll find basic pagination options.

Requested Article:

An efficient deep Convolutional Neural Network based detection and classification of Acute Lymphoblastic Leukemia
Pradeep Kumar Das, Sukadev Meher
Expert Systems with Applications (2021) Vol. 183, pp. 115311-115311
Closed Access | Times Cited: 124

Showing 1-25 of 124 citing articles:

A Systematic Review on Recent Advancements in Deep and Machine Learning Based Detection and Classification of Acute Lymphoblastic Leukemia
Pradeep Kumar Das, Vora Diya, Sukadev Meher, et al.
IEEE Access (2022) Vol. 10, pp. 81741-81763
Open Access | Times Cited: 90
LeuFeatx: Deep learning–based feature extractor for the diagnosis of acute leukemia from microscopic images of peripheral blood smear
Priyanka Rastogi, Kavita Khanna, Vijendra Singh
Computers in Biology and Medicine (2022) Vol. 142, pp. 105236-105236
Closed Access | Times Cited: 83
High accuracy hybrid CNN classifiers for breast cancer detection using mammogram and ultrasound datasets
Adyasha Sahu, Pradeep Kumar Das, Sukadev Meher
Biomedical Signal Processing and Control (2022) Vol. 80, pp. 104292-104292
Closed Access | Times Cited: 81
An efficient deep learning scheme to detect breast cancer using mammogram and ultrasound breast images
Adyasha Sahu, Pradeep Kumar Das, Sukadev Meher
Biomedical Signal Processing and Control (2023) Vol. 87, pp. 105377-105377
Closed Access | Times Cited: 64
A Deep Learning Framework for Leukemia Cancer Detection in Microscopic Blood Samples Using Squeeze and Excitation Learning
Maryam Bukhari, Sadaf Yasmin, Saima Sammad, et al.
Mathematical Problems in Engineering (2022) Vol. 2022, pp. 1-18
Open Access | Times Cited: 69
A lightweight deep learning system for automatic detection of blood cancer
Pradeep Kumar Das, Biswajit Nayak, Sukadev Meher
Measurement (2022) Vol. 191, pp. 110762-110762
Closed Access | Times Cited: 59
An Efficient Detection and Classification of Acute Leukemia Using Transfer Learning and Orthogonal Softmax Layer-Based Model
Pradeep Kumar Das, Biswajeet Sahoo, Sukadev Meher
IEEE/ACM Transactions on Computational Biology and Bioinformatics (2022) Vol. 20, Iss. 3, pp. 1817-1828
Closed Access | Times Cited: 55
A Systematic Review on Acute Leukemia Detection Using Deep Learning Techniques
Rohini Raina, Naveen Kumar Gondhi, Chaahat, et al.
Archives of Computational Methods in Engineering (2022) Vol. 30, Iss. 1, pp. 251-270
Closed Access | Times Cited: 41
Recent advancements in machine learning and deep learning-based breast cancer detection using mammograms
Adyasha Sahu, Pradeep Kumar Das, Sukadev Meher
Physica Medica (2023) Vol. 114, pp. 103138-103138
Open Access | Times Cited: 32
Deep Learning for the Detection of Acute Lymphoblastic Leukemia Subtypes on Microscopic Images: A Systematic Literature Review
Tanzilal Mustaqim, Chastine Fatichah, Nanik Suciati
IEEE Access (2023) Vol. 11, pp. 16108-16127
Open Access | Times Cited: 29
Medical images classification using deep learning: a survey
Rakesh Kumar, Pooja Kumbharkar, Sandeep Vanam, et al.
Multimedia Tools and Applications (2023) Vol. 83, Iss. 7, pp. 19683-19728
Closed Access | Times Cited: 28
Knowledge distillation model for Acute Lymphoblastic Leukemia Detection: Exploring the impact of nesterov-accelerated adaptive moment estimation optimizer
Esraa Hassan, Abeer Saber, Samar Elbedwehy
Biomedical Signal Processing and Control (2024) Vol. 94, pp. 106246-106246
Closed Access | Times Cited: 16
An attention-based deep learning for acute lymphoblastic leukemia classification
Malathy Jawahar, L. Jani Anbarasi, Sathiya Narayanan, et al.
Scientific Reports (2024) Vol. 14, Iss. 1
Open Access | Times Cited: 10
An efficient deep learning network with orthogonal softmax layer for automatic detection of tuberculosis
Pradeep Kumar Das, S Sreevatsav, Ajith Abraham
Engineering Applications of Artificial Intelligence (2024) Vol. 133, pp. 108116-108116
Closed Access | Times Cited: 9
Deep learning methods evaluation to predict air quality based on Computational Fluid Dynamics
Xavier Jurado, Nicolas Reiminger, Marouane Benmoussa, et al.
Expert Systems with Applications (2022) Vol. 203, pp. 117294-117294
Open Access | Times Cited: 31
AIMIC: Deep Learning for Microscopic Image Classification
Rui Liu, Wei Dai, Tianyi Wu, et al.
Computer Methods and Programs in Biomedicine (2022) Vol. 226, pp. 107162-107162
Closed Access | Times Cited: 31
Optimizing a Deep Residual Neural Network with Genetic Algorithm for Acute Lymphoblastic Leukemia Classification
Larissa Ferreira Rodrigues Moreira, André Ricardo Backes, Bruno Augusto Nassif Travençolo, et al.
Journal of Digital Imaging (2022) Vol. 35, Iss. 3, pp. 623-637
Open Access | Times Cited: 30
DeepLeukNet—A CNN based microscopy adaptation model for acute lymphoblastic leukemia classification
Umair Saeed, Kamlesh Kumar, Mansoor Ahmed Khuhro, et al.
Multimedia Tools and Applications (2023) Vol. 83, Iss. 7, pp. 21019-21043
Closed Access | Times Cited: 21
Gaussian Blurring Technique for Detecting and Classifying Acute Lymphoblastic Leukemia Cancer Cells from Microscopic Biopsy Images
Tulasi Gayatri Devi, Nagamma Patil, Sharada Rai, et al.
Life (2023) Vol. 13, Iss. 2, pp. 348-348
Open Access | Times Cited: 20
DSCNet: Deep Skip Connections-Based Dense Network for ALL Diagnosis Using Peripheral Blood Smear Images
Manjit Kaur, Ahmad Ali AlZubi, Arpit Jain, et al.
Diagnostics (2023) Vol. 13, Iss. 17, pp. 2752-2752
Open Access | Times Cited: 19
Comparative analysis of machine learning and deep learning models for improved cancer detection: A comprehensive review of recent advancements in diagnostic techniques
Hari Mohan, Joon Yoo, Abdul Razaque
Expert Systems with Applications (2024) Vol. 255, pp. 124838-124838
Closed Access | Times Cited: 8
Acute lymphocytic leukemia detection and subtype classification via extended wavelet pooling based-CNNs and statistical-texture features
Omneya Attallah
Image and Vision Computing (2024) Vol. 147, pp. 105064-105064
Closed Access | Times Cited: 6
A review of convolutional neural network based methods for medical image classification
Chao Chen, Nor Ashidi Mat Isa, Xin Liu
Computers in Biology and Medicine (2024) Vol. 185, pp. 109507-109507
Closed Access | Times Cited: 6
Transfer Learning-Based Automatic Detection of Acute Lymphocytic Leukemia
Pradeep Kumar Das, Sukadev Meher
(2021)
Closed Access | Times Cited: 36
Assessing the impact of data augmentation and a combination of CNNs on leukemia classification
Maíla L. Claro, Rodrigo Veras, André M. Santana, et al.
Information Sciences (2022) Vol. 609, pp. 1010-1029
Closed Access | Times Cited: 28
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