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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:

Multi-label transfer learning for the early diagnosis of breast cancer
Hiba Chougrad, Hamid Zouaki, Omar Alheyane
Neurocomputing (2019) Vol. 392, pp. 168-180
Closed Access | Times Cited: 96

Showing 1-25 of 96 citing articles:

A Transfer Learning Approach for Early Diagnosis of Alzheimer’s Disease on MRI Images
Atif Mehmood, Shuyuan Yang, Zhixi Feng, et al.
Neuroscience (2021) Vol. 460, pp. 43-52
Open Access | Times Cited: 212
Breast cancer detection using artificial intelligence techniques: A systematic literature review
Ali Bou Nassif, Manar Abu Talib, Qassim Nasir, et al.
Artificial Intelligence in Medicine (2022) Vol. 127, pp. 102276-102276
Open Access | Times Cited: 207
A Review of Deep Learning on Medical Image Analysis
Jian Wang, Hengde Zhu, Shuihua Wang‎, et al.
Mobile Networks and Applications (2020) Vol. 26, Iss. 1, pp. 351-380
Closed Access | Times Cited: 191
Machine learning-based lung and colon cancer detection using deep feature extraction and ensemble learning
Md. Alamin Talukder, Md. Manowarul Islam, Md Ashraf Uddin, et al.
Expert Systems with Applications (2022) Vol. 205, pp. 117695-117695
Open Access | Times Cited: 169
A framework for breast cancer classification using Multi-DCNNs
Dina A. Ragab, Omneya Attallah, Maha Sharkas, et al.
Computers in Biology and Medicine (2021) Vol. 131, pp. 104245-104245
Open Access | Times Cited: 145
Artificial intelligence-based multi-omics analysis fuels cancer precision medicine
Xiujing He, Xiaowei Liu, Fengli Zuo, et al.
Seminars in Cancer Biology (2022) Vol. 88, pp. 187-200
Open Access | Times Cited: 142
Deep Learning Based Methods for Breast Cancer Diagnosis: A Systematic Review and Future Direction
Maged Nasser, Umi Kalsom Yusof
Diagnostics (2023) Vol. 13, Iss. 1, pp. 161-161
Open Access | Times Cited: 110
Image Augmentation Techniques for Mammogram Analysis
Parita Oza, Paawan Sharma, Samir Patel, et al.
Journal of Imaging (2022) Vol. 8, Iss. 5, pp. 141-141
Open Access | Times Cited: 68
Vision-Transformer-Based Transfer Learning for Mammogram Classification
Gelan Ayana, Kokeb Dese, Yisak Dereje, et al.
Diagnostics (2023) Vol. 13, Iss. 2, pp. 178-178
Open Access | Times Cited: 54
Co-design of Human-centered, Explainable AI for Clinical Decision Support
Cecilia Panigutti, Andrea Beretta, Daniele Fadda, et al.
ACM Transactions on Interactive Intelligent Systems (2023) Vol. 13, Iss. 4, pp. 1-35
Open Access | Times Cited: 40
Deep Neural Networks With Region-Based Pooling Structures for Mammographic Image Classification
Xin Shu, Lei Zhang, Zizhou Wang, et al.
IEEE Transactions on Medical Imaging (2020) Vol. 39, Iss. 6, pp. 2246-2255
Closed Access | Times Cited: 131
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
COVID-19 detection in chest X-ray images using deep boosted hybrid learning
Saddam Hussain Khan, Anabia Sohail, Asifullah Khan, et al.
Computers in Biology and Medicine (2021) Vol. 137, pp. 104816-104816
Open Access | Times Cited: 73
Federated transfer learning: Concept and applications
Sudipan Saha, Tahir Ahmad
Intelligenza Artificiale (2021) Vol. 15, Iss. 1, pp. 35-44
Open Access | Times Cited: 72
Coronavirus disease analysis using chest X-ray images and a novel deep convolutional neural network
Saddam Hussain Khan, Anabia Sohail, Muhammad Mohsin Zafar, et al.
Photodiagnosis and Photodynamic Therapy (2021) Vol. 35, pp. 102473-102473
Open Access | Times Cited: 60
Deep convolutional neural networks for computer-aided breast cancer diagnostic: a survey
Parita Oza, Paawan Sharma, Samir Patel, et al.
Neural Computing and Applications (2022) Vol. 34, Iss. 3, pp. 1815-1836
Closed Access | Times Cited: 60
A survey of multi-label classification based on supervised and semi-supervised learning
Meng Han, Hongxin Wu, Zhiqiang Chen, et al.
International Journal of Machine Learning and Cybernetics (2022) Vol. 14, Iss. 3, pp. 697-724
Closed Access | Times Cited: 48
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
Multiscale dense convolutional neural network for DSA cerebrovascular segmentation
Meng Cai, Kai Sun, Shaoya Guan, et al.
Neurocomputing (2019) Vol. 373, pp. 123-134
Closed Access | Times Cited: 58
Hybrid classical–quantum Convolutional Neural Network for stenosis detection in X-ray coronary angiography
Emmanuel Ovalle-Magallanes, Juan Gabriel Avina‐Cervantes, Ivan Cruz‐Aceves, et al.
Expert Systems with Applications (2021) Vol. 189, pp. 116112-116112
Closed Access | Times Cited: 52
BUViTNet: Breast Ultrasound Detection via Vision Transformers
Gelan Ayana, Se‐woon Choe
Diagnostics (2022) Vol. 12, Iss. 11, pp. 2654-2654
Open Access | Times Cited: 35
MIC: Breast Cancer Multi-label Diagnostic Framework Based on Multi-modal Fusion Interaction
Ziyan Chen, Sanli Yi
Deleted Journal (2025)
Closed Access
Transfer Learning for Cancer Diagnosis in Medical Images: A Compendious Study
Navreet Kaur, Rahul Hans
International Journal of Computational Intelligence Systems (2025) Vol. 18, Iss. 1
Open Access
Local Extremum Mapping for Weak Supervision Learning on Mammogram Classification and Localization
Minjuan Zhu, Lei Zhang, Lituan Wang, et al.
Bioengineering (2025) Vol. 12, Iss. 4, pp. 325-325
Open Access
Regularizing extreme learning machine by dual locally linear embedding manifold learning for training multi-label neural network classifiers
Mohammad Rezaei-Ravari, Mahdi Eftekhari, Farid Saberi-Movahed
Engineering Applications of Artificial Intelligence (2020) Vol. 97, pp. 104062-104062
Closed Access | Times Cited: 45
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