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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:

An automated confirmatory system for analysis of mammograms
Wei Peng, René V. Mayorga, Esam M.A. Hussein
Computer Methods and Programs in Biomedicine (2015) Vol. 125, pp. 134-144
Closed Access | Times Cited: 40

Showing 1-25 of 40 citing articles:

Diagnostic accuracy of deep learning in medical imaging: a systematic review and meta-analysis
Ravi Aggarwal, Viknesh Sounderajah, Guy Martin, et al.
npj Digital Medicine (2021) Vol. 4, Iss. 1
Open Access | Times Cited: 542
Deep Convolutional Neural Networks for breast cancer screening
Hiba Chougrad, Hamid Zouaki, Omar Alheyane
Computer Methods and Programs in Biomedicine (2018) Vol. 157, pp. 19-30
Closed Access | Times Cited: 407
Machine learning techniques for breast cancer computer aided diagnosis using different image modalities: A systematic review
Nisreen I. R. Yassin, Shaimaa Omran, Enas M. F. El Houby, et al.
Computer Methods and Programs in Biomedicine (2017) Vol. 156, pp. 25-45
Closed Access | Times Cited: 333
Deep and machine learning techniques for medical imaging-based breast cancer: A comprehensive review
Essam H. Houssein, Marwa M. Emam, Abdelmgeid A. Ali, et al.
Expert Systems with Applications (2020) Vol. 167, pp. 114161-114161
Closed Access | Times Cited: 307
Involvement of Machine Learning for Breast Cancer Image Classification: A Survey
Abdullah-Al Nahid, Yinan Kong
Computational and Mathematical Methods in Medicine (2017) Vol. 2017, pp. 1-29
Open Access | Times Cited: 119
Histopathological Breast-Image Classification Using Local and Frequency Domains by Convolutional Neural Network
Abdullah-Al Nahid, Yinan Kong
Information (2018) Vol. 9, Iss. 1, pp. 19-19
Open Access | Times Cited: 110
A Brief Survey on Breast Cancer Diagnostic With Deep Learning Schemes Using Multi-Image Modalities
Tariq Mahmood, Jianqiang Li, Yan Pei, et al.
IEEE Access (2020) Vol. 8, pp. 165779-165809
Open Access | Times Cited: 103
Deep feature–based automatic classification of mammograms
Ridhi Arora, P. Naresh Kumar, Balasubramanian Raman
Medical & Biological Engineering & Computing (2020) Vol. 58, Iss. 6, pp. 1199-1211
Closed Access | Times Cited: 78
A Systematic Literature Review of Breast Cancer Diagnosis Using Machine Intelligence Techniques
Varsha Nemade, Sunil Pathak, Ashutosh Kumar Dubey
Archives of Computational Methods in Engineering (2022) Vol. 29, Iss. 6, pp. 4401-4430
Closed Access | Times Cited: 42
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
A Review of Machine Learning Techniques for the Classification and Detection of Breast Cancer from Medical Images
Reem Jalloul, H. K. Chethan, Ramez Alkhatib
Diagnostics (2023) Vol. 13, Iss. 14, pp. 2460-2460
Open Access | Times Cited: 21
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: 67
A survey on applying machine learning techniques for management of diseases
Enas M. F. El Houby
Journal of Applied Biomedicine (2018) Vol. 16, Iss. 3, pp. 165-174
Closed Access | Times Cited: 64
Uncertainty-Aware Semi-Supervised Method for Pectoral Muscle Segmentation
Yutao Tang, Yongze Guo, Huayu Wang, et al.
Bioengineering (2025) Vol. 12, Iss. 1, pp. 36-36
Open Access
Density-wise two stage mammogram classification using texture exploiting descriptors
Aditya Shastri, Deepti Tamrakar, Kapil Ahuja
Expert Systems with Applications (2018) Vol. 99, pp. 71-82
Open Access | Times Cited: 45
Convolutional neural network for breast cancer diagnosis using diffuse optical tomography
Qiwen Xu, Xin Wang, Huabei Jiang
Visual Computing for Industry Biomedicine and Art (2019) Vol. 2, Iss. 1
Open Access | Times Cited: 41
A wrapper-based feature selection approach to investigate potential biomarkers for early detection of breast cancer
Majdi Alnowami, Fouad A. Abolaban, Eslam Taha
Journal of Radiation Research and Applied Sciences (2022) Vol. 15, Iss. 1, pp. 104-110
Open Access | Times Cited: 18
Ensemble Feature Extraction with Classification Integrated with Mask RCNN Architecture in Breast Cancer Detection Based on Deep Learning Techniques
S. Prasath Alias Surendhar, R. Kishore Kanna, R. Indumathi
SN Computer Science (2023) Vol. 4, Iss. 5
Closed Access | Times Cited: 10
A Review and Computational Analysis of Breast Cancer Using Different Machine Learning Techniques
Varsha Nemade, Sunil Pathak, Ashutosh Kumar Dubey, et al.
International Journal of Emerging Technology and Advanced Engineering (2022) Vol. 12, Iss. 3, pp. 111-118
Open Access | Times Cited: 16
Classification of Mammograms Using Convolutional Neural Network Based Feature Extraction
Taye Girma Debelee, Mohammadreza Amirian, Achim Ibenthal, et al.
Springer eBooks (2018), pp. 89-98
Closed Access | Times Cited: 31
A systematic review of machine and deep learning techniques for the identification and classification of breast cancer through medical image modalities
Neha Thakur, Pardeep Kumar, A. P. Siva Kumar
Multimedia Tools and Applications (2023) Vol. 83, Iss. 12, pp. 35849-35942
Closed Access | Times Cited: 8
Contrast enhancement in mammograms using homomorphic filter technique
P. S. Vikhe, V. R. Thool
(2016), pp. 1-5
Closed Access | Times Cited: 20
Deep‐features with Bayesian optimized classifiers for the breast cancer diagnosis
S. R. Sannasi Chakravarthy, Harikumar Rajaguru
International Journal of Imaging Systems and Technology (2021) Vol. 31, Iss. 4, pp. 1861-1881
Closed Access | Times Cited: 13
Qualitative assessment of image enhancement algorithms for mammograms based on minimum EDV
Mazin N. Farhan, Mohammed G. Ayoub, Hassan M. Qassim, et al.
TELKOMNIKA (Telecommunication Computing Electronics and Control) (2020) Vol. 18, Iss. 2, pp. 928-928
Open Access | Times Cited: 6
Classification of medical images based on deep stacked patched auto-encoders
Ramzi Ben Ali, Ridha Ejbali, Mourad Zaied
Multimedia Tools and Applications (2020) Vol. 79, Iss. 35-36, pp. 25237-25257
Closed Access | Times Cited: 6
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