Open Access Helper

OpenAlex Citation Counts

OpenAlex Citations Logo

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:

Automatic Detection and Classification of Mammograms Using Improved Extreme Learning Machine with Deep Learning
S. R. Sannasi Chakravarthy, Harikumar Rajaguru
IRBM (2021) Vol. 43, Iss. 1, pp. 49-61
Closed Access | Times Cited: 91

Showing 1-25 of 91 citing articles:

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: 78
Computer-aided breast cancer detection and classification in mammography: A comprehensive review
Kosmia Loizidou, Rafaella Elia, Costas Pitris
Computers in Biology and Medicine (2023) Vol. 153, pp. 106554-106554
Open Access | Times Cited: 75
Deep Learning-Based Metaheuristic Weighted K-Nearest Neighbor Algorithm for the Severity Classification of Breast Cancer
S. R. Sannasi Chakravarthy, N. Bharanidharan, Harikumar Rajaguru
IRBM (2023) Vol. 44, Iss. 3, pp. 100749-100749
Closed Access | Times Cited: 50
A novel fusion framework of deep bottleneck residual convolutional neural network for breast cancer classification from mammogram images
Kiran Jabeen, Muhammad Attique Khan, Mohamed Abdel Hameed, et al.
Frontiers in Oncology (2024) Vol. 14
Open Access | Times Cited: 21
Breast Tumor Classification with Enhanced Transfer Learning Features and Selection Using Chaotic Map-Based Optimization
S. R. Sannasi Chakravarthy, N. Bharanidharan, V. Vinoth Kumar, et al.
International Journal of Computational Intelligence Systems (2024) Vol. 17, Iss. 1
Open Access | Times Cited: 18
Breast cancer diagnosis: A systematic review
Xin Wen, Xing Guo, Shuihua Wang‎, et al.
Journal of Applied Biomedicine (2024) Vol. 44, Iss. 1, pp. 119-148
Open Access | Times Cited: 17
Runoff prediction using a multi-scale two-phase processing hybrid model
Xuehua Zhao, Huifang Wang, Qiucen Guo, et al.
Stochastic Environmental Research and Risk Assessment (2025)
Closed Access | Times Cited: 2
Breast Cancer Detection using Convolutional Autoencoder with Hybrid Deep Learning Model
S. Ranjana, A. Meenakshi
International Journal of Computational and Experimental Science and Engineering (2025) Vol. 11, Iss. 1
Open Access | Times Cited: 2
Multi-Deep CNN based Experimentations for Early Diagnosis of Breast Cancer
S. R. Sannasi Chakravarthy, N. Bharanidharan, Harikumar Rajaguru
IETE Journal of Research (2022) Vol. 69, Iss. 10, pp. 7326-7341
Closed Access | Times Cited: 67
Breast Cancer Mammograms Classification Using Deep Neural Network and Entropy-Controlled Whale Optimization Algorithm
Saliha Zahoor, Umar Shoaib, Ikram Ullah Lali
Diagnostics (2022) Vol. 12, Iss. 2, pp. 557-557
Open Access | Times Cited: 63
Breast Cancer Detection in Mammography Images Using Deep Convolutional Neural Networks and Fuzzy Ensemble Modeling Techniques
Ayman Altameem, Chandrakanta Mahanty, Ramesh Chandra Poonia, et al.
Diagnostics (2022) Vol. 12, Iss. 8, pp. 1812-1812
Open Access | Times Cited: 60
Efficient breast cancer mammograms diagnosis using three deep neural networks and term variance
Ahmed S. Elkorany, Zeinab F. Elsharkawy
Scientific Reports (2023) Vol. 13, Iss. 1
Open Access | Times Cited: 35
Cancer detection and segmentation using machine learning and deep learning techniques: a review
Hari Mohan
Multimedia Tools and Applications (2023) Vol. 83, Iss. 9, pp. 27001-27035
Closed Access | Times Cited: 33
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
Mammography with deep learning for breast cancer detection
Lulu Wang
Frontiers in Oncology (2024) Vol. 14
Open Access | Times Cited: 15
Deep transfer learning with fuzzy ensemble approach for the early detection of breast cancer
S. R. Sannasi Chakravarthy, N. Bharanidharan, V. Vinoth Kumar, et al.
BMC Medical Imaging (2024) Vol. 24, Iss. 1
Open Access | Times Cited: 8
Fast discrete curvelet transform and modified PSO based improved evolutionary extreme learning machine for breast cancer detection
Debendra Muduli, Ratnakar Dash, Banshidhar Majhi
Biomedical Signal Processing and Control (2021) Vol. 70, pp. 102919-102919
Closed Access | Times Cited: 51
An integrated framework for breast mass classification and diagnosis using stacked ensemble of residual neural networks
Asma Baccouche, Begonya García-Zapirain, Adel Elmaghraby
Scientific Reports (2022) Vol. 12, Iss. 1
Open Access | Times Cited: 32
Intelligent quantification of natural gas pipeline defects using improved sparrow search algorithm and deep extreme learning machine
Jingyi Xiong, Wei Liang, Xiaobin Liang, et al.
Process Safety and Environmental Protection (2022) Vol. 183, pp. 567-579
Closed Access | Times Cited: 30
ETECADx: Ensemble Self-Attention Transformer Encoder for Breast Cancer Diagnosis Using Full-Field Digital X-ray Breast Images
Aymen M. Al-Hejri, Riyadh M. Al-Tam, Muneer Fazea, et al.
Diagnostics (2022) Vol. 13, Iss. 1, pp. 89-89
Open Access | Times Cited: 30
A comprehensive analysis of recent advancements in cancer detection using machine learning and deep learning models for improved diagnostics
Hari Mohan, Joon Yoo
Journal of Cancer Research and Clinical Oncology (2023) Vol. 149, Iss. 15, pp. 14365-14408
Closed Access | Times Cited: 21
Development of an Artificial Intelligence-Based Breast Cancer Detection Model by Combining Mammograms and Medical Health Records
Nguyen Thi Hoang Trang, Khương Quỳnh Long, Pham Lê An, et al.
Diagnostics (2023) Vol. 13, Iss. 3, pp. 346-346
Open Access | Times Cited: 17
Applying Explainable Machine Learning Models for Detection of Breast Cancer Lymph Node Metastasis in Patients Eligible for Neoadjuvant Treatment
Josip Vrdoljak, Zvonimir Boban, Domjan Barić, et al.
Cancers (2023) Vol. 15, Iss. 3, pp. 634-634
Open Access | Times Cited: 17
ALBAE feature extraction based lung pneumonia and cancer classification
M. Braveen, S. Nachiyappan, R Seetha, et al.
Soft Computing (2023) Vol. 28, Iss. S2, pp. 589-589
Open Access | Times Cited: 17
An Improved Classification of Pork Adulteration in Beef Based on Electronic Nose Using Modified Deep Extreme Learning with Principal Component Analysis as Feature Learning
Cries Avian, Jenq‐Shiou Leu, Setya Widyawan Prakosa, et al.
Food Analytical Methods (2022) Vol. 15, Iss. 11, pp. 3020-3031
Closed Access | Times Cited: 24
Page 1 - Next Page

Scroll to top