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OpenAlex Citation Counts

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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:

Methods Used in Computer-Aided Diagnosis for Breast Cancer Detection Using Mammograms: A Review
Saleem Z. Ramadan
Journal of Healthcare Engineering (2020) Vol. 2020, pp. 1-21
Open Access | Times Cited: 96

Showing 1-25 of 96 citing articles:

A survey on deep learning in medicine: Why, how and when?
Francesco Piccialli, Vittorio Di Somma, Fabio Giampaolo, et al.
Information Fusion (2020) Vol. 66, pp. 111-137
Closed Access | Times Cited: 287
A Systematic Review of Artificial Intelligence Techniques in Cancer Prediction and Diagnosis
Yogesh Kumar, Surbhi Gupta, Ruchi Singla, et al.
Archives of Computational Methods in Engineering (2021) Vol. 29, Iss. 4, pp. 2043-2070
Open Access | Times Cited: 152
Improved multi-classification of breast cancer histopathological images using handcrafted features and deep neural network (dense layer)
Agaba Ameh Joseph, Mohammed Abdullahi, Sahalu B. Junaidu, et al.
Intelligent Systems with Applications (2022) Vol. 14, pp. 200066-200066
Open Access | Times Cited: 75
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: 72
A Comprehensive Review on Breast Cancer Detection, Classification and Segmentation Using Deep Learning
Barsha Abhisheka, Saroj Kumar Biswas, Biswajit Purkayastha
Archives of Computational Methods in Engineering (2023) Vol. 30, Iss. 8, pp. 5023-5052
Closed Access | Times Cited: 64
BC2NetRF: Breast Cancer Classification from Mammogram Images Using Enhanced Deep Learning Features and Equilibrium-Jaya Controlled Regula Falsi-Based Features Selection
Kiran Jabeen, Muhammad Attique Khan, Jamel Balili, et al.
Diagnostics (2023) Vol. 13, Iss. 7, pp. 1238-1238
Open Access | Times Cited: 55
Breast Cancer Detection Using Mammogram Images with Improved Multi-Fractal Dimension Approach and Feature Fusion
Dilovan Asaad Zebari, Dheyaa Ahmed Ibrahim, Diyar Qader Zeebaree, et al.
Applied Sciences (2021) Vol. 11, Iss. 24, pp. 12122-12122
Open Access | Times Cited: 79
Classification of Hematoxylin and Eosin‐Stained Breast Cancer Histology Microscopy Images Using Transfer Learning with EfficientNets
Chanaleä Munien, Serestina Viriri
Computational Intelligence and Neuroscience (2021) Vol. 2021, Iss. 1
Open Access | Times Cited: 57
Deep learning-based automatic segmentation of images in cardiac radiography: A promising challenge
Yucheng Song, Shengbing Ren, Yu Lu, et al.
Computer Methods and Programs in Biomedicine (2022) Vol. 220, pp. 106821-106821
Closed Access | Times Cited: 52
Efficient breast cancer detection via cascade deep learning network
Bita Asadi, Qurban A. Memon
International Journal of Intelligent Networks (2023) Vol. 4, pp. 46-52
Open Access | Times Cited: 24
CerviLearnNet: Advancing cervical cancer diagnosis with reinforcement learning-enhanced convolutional networks
Shakhnoza Muksimova, Sabina Umirzakova, Seung‐Baik Kang, et al.
Heliyon (2024) Vol. 10, Iss. 9, pp. e29913-e29913
Open Access | Times Cited: 14
Deep-Learning-Based Computer-Aided Systems for Breast Cancer Imaging: A Critical Review
Yuliana Jiménez-Gaona, María José Rodríguez-Álvarez, Vasudevan Lakshminarayanan
Applied Sciences (2020) Vol. 10, Iss. 22, pp. 8298-8298
Open Access | Times Cited: 68
Classification of Breast Cancer Histopathological Images Using DenseNet and Transfer Learning
Musa Adamu Wakili, Harisu Abdullahi Shehu, Md. Haidar Sharif, et al.
Computational Intelligence and Neuroscience (2022) Vol. 2022, pp. 1-31
Open Access | Times Cited: 36
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: 30
Breast cancer detection using machine learning approaches: a comparative study
Muawia A. Elsadig, Abdelrahman Altigani, Huwaida T. Elshoush
International Journal of Power Electronics and Drive Systems/International Journal of Electrical and Computer Engineering (2022) Vol. 13, Iss. 1, pp. 736-736
Open Access | Times Cited: 29
Classification of Breast Cancer Using Transfer Learning and Advanced Al-Biruni Earth Radius Optimization
Amel Ali Alhussan, Abdelaziz A. Abdelhamid, S. K. Towfek, et al.
Biomimetics (2023) Vol. 8, Iss. 3, pp. 270-270
Open Access | Times Cited: 18
EfficientNet family U-Net models for deep learning semantic segmentation of kidney tumors on CT images
Abubaker Abdelrahman, Serestina Viriri
Frontiers in Computer Science (2023) Vol. 5
Open Access | Times Cited: 16
Deep learning approaches for breast cancer detection in histopathology images: A review
Lakshmi Priya C V, Vinai George Biju, B. Vinod, et al.
Cancer Biomarkers (2024) Vol. 40, Iss. 1, pp. 1-25
Open Access | Times Cited: 7
BCDM: A Novel AI-Based Model for Detection of Breast Cancer
Warda M. Shaban, Hossam El-Din Moustafa, Mervat El-Seddek
Lecture notes in networks and systems (2025), pp. 468-479
Closed Access
Classification of Chronic Kidney Disease in Sonography Using the GLCM and Artificial Neural Network
Dong Hyun Kim, Soo-Young Ye
Diagnostics (2021) Vol. 11, Iss. 5, pp. 864-864
Open Access | Times Cited: 37
A review of the current state of the computer-aided diagnosis (CAD) systems for breast cancer diagnosis
Zicheng Guo, Jiping Xie, Yi Wan, et al.
Open Life Sciences (2022) Vol. 17, Iss. 1, pp. 1600-1611
Open Access | Times Cited: 25
Insight into breast cancer detection: new hybrid feature selection method
Warda M. Shaban
Neural Computing and Applications (2022) Vol. 35, Iss. 9, pp. 6831-6853
Open Access | Times Cited: 22
Application of Radiomics Analysis on Mammography for Differentiating Benign and Malignant Masses
Oğuz Lafcı, Erkan Akkur, Pınar Çelepli, et al.
SN Comprehensive Clinical Medicine (2025) Vol. 7, Iss. 1
Closed Access
Detecting and classifying breast masses via YOLO-based deep learning
Büşra Kübra Karaca, Ziya Telatar, Selda Güney, et al.
Neural Computing and Applications (2025)
Open Access
Multi-modal prediction of breast cancer using particle swarm optimization with non-dominating sorting
S. Vijayalakshmi, A John, R. Sunder, et al.
International Journal of Distributed Sensor Networks (2020) Vol. 16, Iss. 11, pp. 155014772097150-155014772097150
Open Access | Times Cited: 37
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