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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:

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

Showing 1-25 of 72 citing articles:

Applications and Techniques of Machine Learning in Cancer Classification: A Systematic Review
Abrar Yaqoob, Rabia Musheer Aziz, Navneet Kumar Verma
Human-Centric Intelligent Systems (2023) Vol. 3, Iss. 4, pp. 588-615
Open Access | Times Cited: 60
BC-QNet: A Quantum-Infused ELM Model for Breast Cancer Diagnosis
Anas Bilal, Azhar Imran, Xiaowen Liu, et al.
Computers in Biology and Medicine (2024) Vol. 175, pp. 108483-108483
Closed Access | Times Cited: 20
Benign and Malignant Breast Tumor Classification in Ultrasound and Mammography Images via Fusion of Deep Learning and Handcraft Features
Clara Cruz-Ramos, Oscar García-Avila, Jose A. Almaraz-Damian, et al.
Entropy (2023) Vol. 25, Iss. 7, pp. 991-991
Open Access | Times Cited: 24
B2C3NetF2: Breast cancer classification using an end‐to‐end deep learning feature fusion and satin bowerbird optimization controlled Newton Raphson feature selection
Mamuna Fatima, Muhammad Attique Khan, Saima Shaheen, et al.
CAAI Transactions on Intelligence Technology (2023) Vol. 8, Iss. 4, pp. 1374-1390
Open Access | Times Cited: 22
Radiomics in breast cancer: Current advances and future directions
Ying-Jia Qi, Guan-Hua Su, Chao You, et al.
Cell Reports Medicine (2024) Vol. 5, Iss. 9, pp. 101719-101719
Open Access | Times Cited: 8
Interpretable Radiomic Signature for Breast Microcalcification Detection and Classification
Francesco Prinzi, Alessia Angela Maria Orlando, Salvatore Gaglio, et al.
Deleted Journal (2024) Vol. 37, Iss. 3, pp. 1038-1053
Open Access | Times Cited: 7
Classification of white blood cells (leucocytes) from blood smear imagery using machine and deep learning models: A global scoping review
Rabia Asghar, Sanjay Kumar, Arslan Shaukat, et al.
PLoS ONE (2024) Vol. 19, Iss. 6, pp. e0292026-e0292026
Open Access | Times Cited: 7
Evaluation of the precision and accuracy in the classification of breast histopathology images using the MobileNetV3 model
Kenneth DeVoe, Gary Takahashi, Ebrahim Tarshizi, et al.
Journal of Pathology Informatics (2024) Vol. 15, pp. 100377-100377
Open Access | Times Cited: 7
An intelligent healthcare framework for breast cancer diagnosis based on the information fusion of novel deep learning architectures and improved optimization algorithm
Kiran Jabeen, Muhammad Attique Khan, Robertas Damaševičius, et al.
Engineering Applications of Artificial Intelligence (2024) Vol. 137, pp. 109152-109152
Closed Access | Times Cited: 6
Deep learning approaches to detect breast cancer: a comprehensive review
Amir Mohammad Sharafaddini, Kiana Kouhpah Esfahani, N. Mansouri
Multimedia Tools and Applications (2024)
Closed Access | Times Cited: 5
XAI-RACapsNet: Relevance aware capsule network-based breast cancer detection using mammography images via explainability O-net ROI segmentation
Ahmad Alhussen, Mohd Anul Haq, Arfat Ahmad Khan, et al.
Expert Systems with Applications (2024), pp. 125461-125461
Closed Access | Times Cited: 5
Two-stage CNN-based framework for leukocytes classification
Siraj M. Khan, Muhammad Sajjad, José Escorcia‐Gutierrez, et al.
Computers in Biology and Medicine (2025) Vol. 187, pp. 109616-109616
Closed Access
Detection of Masses in Mammogram Images Based on the Enhanced RetinaNet Network With INbreast Dataset
Mingzhao Wang, Ran Liu, Joseph Luttrell, et al.
Journal of Multidisciplinary Healthcare (2025) Vol. Volume 18, pp. 675-695
Open Access
Hybrid Deep Learning and Active Contour Approach for Enhanced Breast Lesion Segmentation and Classification in Mammograms
Abdala Nour, Boubakeur Boufama
Intelligence-Based Medicine (2025) Vol. 11, pp. 100224-100224
Open Access
A Hybrid Deep Learning Approach for Breast Cancer Classification Based on Histology Images
Sameh Zarif, Hatem Abdul-Kader, Ibrahim Sayed Elaraby, et al.
Lecture notes on data engineering and communications technologies (2025), pp. 265-274
Closed Access
Optimizing Artificial Intelligence-aided breast cancer models: An empirical analysis of binary classifiers and regression-based feature selectors
Fakhriddin Madolimov, Asilbek Medatov, Elmira Nazirova, et al.
Engineering Applications of Artificial Intelligence (2025) Vol. 147, pp. 110318-110318
Closed Access
Subtraction of Temporally Sequential Digital Mammograms: Prediction and Localization of Near-Term Breast Cancer Occurrence
Kosmia Loizidou, Galateia Skouroumouni, Gabriella Savvidou, et al.
Deleted Journal (2025)
Open Access
PSO-Optimized Fractional Order CNNs for Enhanced Breast Cancer Detection
Abhinay Yadav, Vaegae Naveen Kumar
Results in Engineering (2025), pp. 104559-104559
Open 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
Annotation-efficient, patch-based, explainable deep learning using curriculum method for breast cancer detection in screening mammography
Ozden Camurdan, Toygar Tanyel, Esma Çerekçi, et al.
Insights into Imaging (2025) Vol. 16, Iss. 1
Open Access
A comprehensive survey of intestine histopathological image analysis using machine vision approaches
Yujie Jing, Chen Li, Tianming Du, et al.
Computers in Biology and Medicine (2023) Vol. 165, pp. 107388-107388
Closed Access | Times Cited: 13
The application of traditional machine learning and deep learning techniques in mammography: a review
Ying’e Gao, Jingjing Lin, Yuzhuo Zhou, et al.
Frontiers in Oncology (2023) Vol. 13
Open Access | Times Cited: 12
Artificial Intelligence Techniques and Pedigree Charts in Oncogenetics: Towards an Experimental Multioutput Software System for Digitization and Risk Prediction
Luana Conte, Emanuele Rizzo, Tiziana Grassi, et al.
Computation (2024) Vol. 12, Iss. 3, pp. 47-47
Open Access | Times Cited: 4
Breast Cancer Diagnosis Using YOLO-Based Multiscale Parallel CNN and Flattened Threshold Swish
Ahmed Dhahi Mohammed, Dursun Ekmekci
Applied Sciences (2024) Vol. 14, Iss. 7, pp. 2680-2680
Open Access | Times Cited: 4
Multimodal breast cancer hybrid explainable computer-aided diagnosis using medical mammograms and ultrasound Images
Riyadh M. Al-Tam, Aymen M. Al-Hejri, Sultan S. Alshamrani, et al.
Journal of Applied Biomedicine (2024) Vol. 44, Iss. 3, pp. 731-758
Closed Access | Times Cited: 4
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