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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:

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

Showing 1-25 of 67 citing articles:

Breast Cancer Classification from Ultrasound Images Using Probability-Based Optimal Deep Learning Feature Fusion
Kiran Jabeen, Muhammad Attique Khan, Majed Alhaisoni, et al.
Sensors (2022) Vol. 22, Iss. 3, pp. 807-807
Open Access | Times Cited: 197
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
Breast cancer detection using deep learning techniques: challenges and future directions
Muhammad Shahid, Azhar Imran
Multimedia Tools and Applications (2025)
Closed Access | Times Cited: 2
Systematic Review of Computing Approaches for Breast Cancer Detection Based Computer Aided Diagnosis Using Mammogram Images
Dilovan Asaad Zebari, Dheyaa Ahmed Ibrahim, Diyar Qader Zeebaree, et al.
Applied Artificial Intelligence (2021) Vol. 35, Iss. 15, pp. 2157-2203
Open Access | Times Cited: 80
Computer-aided diagnosis for breast cancer detection and classification using optimal region growing segmentation with MobileNet model
J. Dafni Rose, K. Vijayakumar, Laxman Singh, et al.
Concurrent Engineering (2022) Vol. 30, Iss. 2, pp. 181-189
Closed Access | Times Cited: 45
A deep learning approach for automatic detection, segmentation and classification of breast lesions from thermal images
Soner ÇİVİLİBAL, Kerim Kürşat Çevi̇k, Ahmet Bozkurt
Expert Systems with Applications (2022) Vol. 212, pp. 118774-118774
Closed Access | Times Cited: 40
Breast cancer classification using deep learned features boosted with handcrafted features
Unaiza Sajid, Rizwan Ahmed Khan, Shahid Munir Shah, et al.
Biomedical Signal Processing and Control (2023) Vol. 86, pp. 105353-105353
Open Access | Times Cited: 29
A New Deep-Learning-Based Model for Breast Cancer Diagnosis from Medical Images
Salman Zakareya, Habib Izadkhah, Jaber Karimpour
Diagnostics (2023) Vol. 13, Iss. 11, pp. 1944-1944
Open Access | Times Cited: 26
Informed consent for artificial intelligence in emergency medicine: A practical guide
Kenneth V. Iserson
The American Journal of Emergency Medicine (2023) Vol. 76, pp. 225-230
Closed Access | Times Cited: 24
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
Gan-based data augmentation to improve breast ultrasound and mammography mass classification
Yuliana Jiménez-Gaona, Diana Carrión-Figueroa, Vasudevan Lakshminarayanan, et al.
Biomedical Signal Processing and Control (2024) Vol. 94, pp. 106255-106255
Open Access | Times Cited: 7
Automated breast tumor ultrasound image segmentation with hybrid UNet and classification using fine-tuned CNN model
Shahed Hossain, Sami Azam, Sidratul Montaha, et al.
Heliyon (2023) Vol. 9, Iss. 11, pp. e21369-e21369
Open Access | Times Cited: 19
BraNet: a mobil application for breast image classification based on deep learning algorithms
Yuliana Jiménez-Gaona, María José Rodríguez Álvarez, Darwin Castillo, et al.
Medical & Biological Engineering & Computing (2024) Vol. 62, Iss. 9, pp. 2737-2756
Open Access | Times Cited: 5
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
Explainable Ensemble Machine Learning for Breast Cancer Diagnosis Based on Ultrasound Image Texture Features
Alireza Rezazadeh, Yasamin Jafarian, Ali Kord Valeshabad
Forecasting (2022) Vol. 4, Iss. 1, pp. 262-274
Open Access | Times Cited: 22
Multi-view stereoscopic attention network for 3D tumor classification in automated breast ultrasound
Wanli Ding, Heye Zhang, Shuxin Zhuang, et al.
Expert Systems with Applications (2023) Vol. 234, pp. 120969-120969
Closed Access | Times Cited: 14
Augmented Reality-Assisted Ultrasound Breast Biopsy
Nuno Costa, Luís Ferreira, Augusto Righetti Vieira Ferreira de Araújo, et al.
Sensors (2023) Vol. 23, Iss. 4, pp. 1838-1838
Open Access | Times Cited: 13
Deep learning and genetic algorithm-based ensemble model for feature selection and classification of breast ultrasound images
Mohsin Furkh Dar, Avatharam Ganivada
Image and Vision Computing (2024) Vol. 146, pp. 105018-105018
Closed Access | Times Cited: 4
Bridging healthcare gaps: a scoping review on the role of artificial intelligence, deep learning, and large language models in alleviating problems in medical deserts
Zdeslav Strika, Karlo Petković, Robert Likić, et al.
Postgraduate Medical Journal (2024)
Closed Access | Times Cited: 4
An Efficient Transfer and Ensemble Learning Based Computer Aided Breast Abnormality Diagnosis System
Farnoosh Azour, Azzedine Boukerche
IEEE Access (2022) Vol. 11, pp. 21199-21209
Open Access | Times Cited: 19
Medical image analysis of masses in mammography using deep learning model for early diagnosis of cancer tissues
Rita Maria Silva Julia, Shajin Prince, Davide Bini
Elsevier eBooks (2024), pp. 75-89
Closed Access | Times Cited: 3
MR Images, Brain Lesions, and Deep Learning
Darwin Castillo, Vasudevan Lakshminarayanan, María José Rodríguez-Álvarez
Applied Sciences (2021) Vol. 11, Iss. 4, pp. 1675-1675
Open Access | Times Cited: 20
Design Guidelines for Mammogram-Based Computer-Aided Systems Using Deep Learning Techniques
Farnoosh Azour, Azzedine Boukerche
IEEE Access (2022) Vol. 10, pp. 21701-21726
Open Access | Times Cited: 15
Computer-Aided Breast Cancer Diagnosis: Comparative Analysis of Breast Imaging Modalities and Mammogram Repositories
Parita Oza, Paawan Sharma, Samir Patel, et al.
Current Medical Imaging Formerly Current Medical Imaging Reviews (2022) Vol. 19, Iss. 5, pp. 456-468
Closed Access | Times Cited: 15
Radiomics Diagnostic Tool Based on Deep Learning for Colposcopy Image Classification
Yuliana Jiménez-Gaona, Darwin Castillo, Bernardo Vega, et al.
Diagnostics (2022) Vol. 12, Iss. 7, pp. 1694-1694
Open Access | Times Cited: 15
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