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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:

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

Showing 1-25 of 119 citing articles:

Deep learning-based breast cancer classification through medical imaging modalities: state of the art and research challenges
Ghulam Murtaza, Liyana Shuib, Ainuddin Wahid Abdul Wahab, et al.
Artificial Intelligence Review (2019) Vol. 53, Iss. 3, pp. 1655-1720
Closed Access | Times Cited: 258
A Deep Learning Method for Breast Cancer Classification in the Pathology Images
Min Liu, Lanlan Hu, Ying Tang, et al.
IEEE Journal of Biomedical and Health Informatics (2022) Vol. 26, Iss. 10, pp. 5025-5032
Closed Access | Times Cited: 87
Recent Trends in Computer Assisted Diagnosis (CAD) System for Breast Cancer Diagnosis Using Histopathological Images
Chetna Kaushal, Shiveta Bhat, Deepika Koundal, et al.
IRBM (2019) Vol. 40, Iss. 4, pp. 211-227
Closed Access | Times Cited: 140
Comparative analysis of breast cancer detection using machine learning and biosensors
Yash Amethiya, Prince Pipariya, Shlok Patel, et al.
Intelligent Medicine (2021) Vol. 2, Iss. 2, pp. 69-81
Open Access | Times Cited: 92
A Comparative Analysis of Nonlinear Machine Learning Algorithms for Breast Cancer Detection
Ali Al Bataineh
International Journal of Machine Learning and Computing (2019) Vol. 9, Iss. 3, pp. 248-254
Open Access | Times Cited: 79
A Deep-Learning Approach for Diagnosis of Metastatic Breast Cancer in Bones from Whole-Body Scans
Νικόλαος Παπανδριανός, Elpiniki I. Papageorgiou, Athanasios Anagnostis, et al.
Applied Sciences (2020) Vol. 10, Iss. 3, pp. 997-997
Open Access | Times Cited: 74
Reviewing Machine Learning and Image Processing Based Decision-Making Systems for Breast Cancer Imaging
Hasnae Zerouaoui, Ali Idri
Journal of Medical Systems (2021) Vol. 45, Iss. 1
Closed Access | Times Cited: 73
Breast histopathological image analysis using image processing techniques for diagnostic purposes: A methodological review
R Rashmi, Keerthana Prasad, Chethana Babu K. Udupa
Journal of Medical Systems (2021) Vol. 46, Iss. 1
Open Access | Times Cited: 62
Breast cancer prediction model with decision tree and adaptive boosting
Tsehay Admassu Assegie, R. Lakshmi Tulasi, N. Komal Kumar
IAES International Journal of Artificial Intelligence (2021) Vol. 10, Iss. 1, pp. 184-184
Open Access | Times Cited: 59
A Comprehensive Survey on Deep-Learning-Based Breast Cancer Diagnosis
M. F. Mridha, Md. Abdul Hamid, Muhammad Mostafa Monowar, et al.
Cancers (2021) Vol. 13, Iss. 23, pp. 6116-6116
Open Access | Times Cited: 57
A deep learning model using data augmentation for detection of architectural distortion in whole and patches of images
Olaide N. Oyelade, Absalom E. Ezugwu
Biomedical Signal Processing and Control (2020) Vol. 65, pp. 102366-102366
Closed Access | Times Cited: 68
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
Analysis of Histopathological Images for Prediction of Breast Cancer Using Traditional Classifiers with Pre-Trained CNN
Karan Gupta, Nidhi Grover Rakesh Chawla
Procedia Computer Science (2020) Vol. 167, pp. 878-889
Open Access | Times Cited: 65
Medical image based breast cancer diagnosis: State of the art and future directions
Mehreen Tariq, Sajid Iqbal, Hareem Ayesha, et al.
Expert Systems with Applications (2020) Vol. 167, pp. 114095-114095
Closed Access | Times Cited: 65
Convolutional neural network for automated mass segmentation in mammography
Dina Abdelhafiz, Jinbo Bi, Reda A. Ammar, et al.
BMC Bioinformatics (2020) Vol. 21, Iss. S1
Open Access | Times Cited: 50
A comparative study of machine learning models with LASSO and SHAP feature selection for breast cancer prediction
Md. Shazzad Hossain Shaon, Tasmin Karim, Shahriar Shakil, et al.
Healthcare Analytics (2024) Vol. 6, pp. 100353-100353
Open Access | Times Cited: 6
Sliding Window Based Support Vector Machine System for Classification of Breast Cancer Using Histopathological Microscopic Images
Amin Alqudah, Ali Mohammad Alqudah
IETE Journal of Research (2019) Vol. 68, Iss. 1, pp. 59-67
Closed Access | Times Cited: 51
A State-of-the-Art Survey on Deep Learning Methods for Detection of Architectural Distortion From Digital Mammography
Olaide N. Oyelade, Absalom E. Ezugwu
IEEE Access (2020) Vol. 8, pp. 148644-148676
Open Access | Times Cited: 47
A Novel Hybrid K-Means and GMM Machine Learning Model for Breast Cancer Detection
P. Esther Jebarani, N Umadevi, Hien Dang, et al.
IEEE Access (2021) Vol. 9, pp. 146153-146162
Open Access | Times Cited: 39
Machine Learning Protocols in Early Cancer Detection Based on Liquid Biopsy: A Survey
Linjing Liu, Xingjian Chen, Olutomilayo Olayemi Petinrin, et al.
Life (2021) Vol. 11, Iss. 7, pp. 638-638
Open Access | Times Cited: 38
Breast Cancer Histopathology Image Classification using AlexNet
Ankit Kumar Titoriya, Shelly Sachdeva
2021 5th International Conference on Information Systems and Computer Networks (ISCON) (2019), pp. 708-712
Closed Access | Times Cited: 41
Mammography Image Quality Assurance Using Deep Learning
Tobias Kretz, Klaus‐Robert Mueller, Tobias Schaeffter, et al.
IEEE Transactions on Biomedical Engineering (2020) Vol. 67, Iss. 12, pp. 3317-3326
Open Access | Times Cited: 34
Deep Learning on Histopathology Images for Breast Cancer Classification: A Bibliometric Analysis
Siti Shaliza Mohd Khairi, Mohd Aftar Abu Bakar, Mohd Almie Alias, et al.
Healthcare (2021) Vol. 10, Iss. 1, pp. 10-10
Open Access | Times Cited: 28
Machine Learning Approach to Quadratic Programming-Based Microwave Imaging for Breast Cancer Detection
Sandra Costanzo, Alexandra Flores, Giovanni Buonanno
Sensors (2022) Vol. 22, Iss. 11, pp. 4122-4122
Open Access | Times Cited: 19
Assessment of the invariance and discriminant power of morphological features under geometric transformations for breast tumor classification
Wilfrido Gómez‐Flores, Juanita Hernández-López
Computer Methods and Programs in Biomedicine (2019) Vol. 185, pp. 105173-105173
Closed Access | Times Cited: 32
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