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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:

A Technical Review of Convolutional Neural Network-Based Mammographic Breast Cancer Diagnosis
Lian Zou, Shaode Yu, Tiebao Meng, et al.
Computational and Mathematical Methods in Medicine (2019) Vol. 2019, pp. 1-16
Open Access | Times Cited: 109

Showing 1-25 of 109 citing articles:

Survey on Machine Learning and Deep Learning Applications in Breast Cancer Diagnosis
Gunjan Chugh, Shailender Kumar, Nanhay Singh
Cognitive Computation (2021) Vol. 13, Iss. 6, pp. 1451-1470
Closed Access | Times Cited: 114
Machine Learning for Lung Cancer Diagnosis, Treatment, and Prognosis
Yawei Li, Wu Xin, Ping Yang, et al.
Genomics Proteomics & Bioinformatics (2022) Vol. 20, Iss. 5, pp. 850-866
Open Access | Times Cited: 93
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
Heart disease classification based on ECG using machine learning models
Seyed Matin Malakouti
Biomedical Signal Processing and Control (2023) Vol. 84, pp. 104796-104796
Closed Access | Times Cited: 60
A bird’s-eye view of deep learning in bioimage analysis
Erik Meijering
Computational and Structural Biotechnology Journal (2020) Vol. 18, pp. 2312-2325
Open Access | Times Cited: 116
Methods Used in Computer-Aided Diagnosis for Breast Cancer Detection Using Mammograms: A Review
Saleem Z. Ramadan
Journal of Healthcare Engineering (2020) Vol. 2020, pp. 1-21
Open Access | Times Cited: 96
Diagnosing of disease using machine learning
Pushpa Singh, Narendra Singh, Krishna Kant Singh, et al.
Elsevier eBooks (2021), pp. 89-111
Closed Access | Times Cited: 89
Facial Recognition System for People with and without Face Mask in Times of the COVID-19 Pandemic
Jonathan S. Talahua, Jorge Buele, Paola Calvopiña, et al.
Sustainability (2021) Vol. 13, Iss. 12, pp. 6900-6900
Open Access | Times Cited: 63
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
Deep Learning Prediction of Ovarian Malignancy at US Compared with O-RADS and Expert Assessment
Hui Chen, Bowen Yang, Le Qian, et al.
Radiology (2022) Vol. 304, Iss. 1, pp. 106-113
Closed Access | Times Cited: 57
A comprehensive survey of deep learning research on medical image analysis with focus on transfer learning
Sema Atasever, Nuh Azgınoglu, Duygu Sinanç Terzi, et al.
Clinical Imaging (2022) Vol. 94, pp. 18-41
Closed Access | Times Cited: 56
A Survey of Convolutional Neural Network in Breast Cancer
Ziquan Zhu, Shuihua Wang‎, Yudong Zhang
Computer Modeling in Engineering & Sciences (2022) Vol. 136, Iss. 3, pp. 2127-2172
Open Access | Times Cited: 40
Evaluation of deep learning models for detecting breast cancer using histopathological mammograms Images
Subasish Mohapatra, Sarmistha Muduly, Subhadarshini Mohanty, et al.
Sustainable Operations and Computers (2022) Vol. 3, pp. 296-302
Open Access | Times Cited: 38
Efficient breast cancer detection via cascade deep learning network
Bita Asadi, Qurban A. Memon
International Journal of Intelligent Networks (2023) Vol. 4, pp. 46-52
Open Access | Times Cited: 24
Enhancing breast cancer segmentation and classification: An Ensemble Deep Convolutional Neural Network and U-net approach on ultrasound images
Md. Rakibul Islam, Md Mahbubur Rahman, Md Shahin Ali, et al.
Machine Learning with Applications (2024) Vol. 16, pp. 100555-100555
Open Access | Times Cited: 10
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: 68
Axillary lymph node metastasis status prediction of early-stage breast cancer using convolutional neural networks
Yan‐Wei Lee, Chiun‐Sheng Huang, Chung-Chih Shih, et al.
Computers in Biology and Medicine (2020) Vol. 130, pp. 104206-104206
Closed Access | Times Cited: 57
Detection of breast cancer by ATR-FTIR spectroscopy using artificial neural networks
Rock Christian Tomas, Anthony Jay Sayat, Andrea Nicole Atienza, et al.
PLoS ONE (2022) Vol. 17, Iss. 1, pp. e0262489-e0262489
Open Access | Times Cited: 32
A drug identification model developed using deep learning technologies: experience of a medical center in Taiwan
Hsien-Wei Ting, Sheng-Luen Chung, Chih-Fang Chen, et al.
BMC Health Services Research (2020) Vol. 20, Iss. 1
Open Access | Times Cited: 41
Review paper on research direction towards cancer prediction and prognosis using machine learning and deep learning models
Satyanarayana Murthy Nimmagadda, Chaitanya Bethala
Journal of Ambient Intelligence and Humanized Computing (2021) Vol. 14, Iss. 5, pp. 5595-5613
Closed Access | Times Cited: 33
Breast cancer detection and classification in mammogram using a three-stage deep learning framework based on PAA algorithm
Jiale Jiang, Junchuan Peng, Chuting Hu, et al.
Artificial Intelligence in Medicine (2022) Vol. 134, pp. 102419-102419
Closed Access | Times Cited: 27
Improving mammography lesion classification by optimal fusion of handcrafted and deep transfer learning features
Meredith Jones, Rowzat Faiz, Yuchen Qiu, et al.
Physics in Medicine and Biology (2022) Vol. 67, Iss. 5, pp. 054001-054001
Open Access | Times Cited: 22
Computational Intelligence in Cancer Diagnostics: A Contemporary Review of Smart Phone Apps, Current Problems, and Future Research Potentials
Somit Jain, Dharmik Naicker, Ritu Raj, et al.
Diagnostics (2023) Vol. 13, Iss. 9, pp. 1563-1563
Open Access | Times Cited: 14
Automatic Prediction of MGMT Status in Glioblastoma via Deep Learning-Based MR Image Analysis
Xin Chen, Min Zeng, Yichen Tong, et al.
BioMed Research International (2020) Vol. 2020, pp. 1-9
Open Access | Times Cited: 38
BIRADS features-oriented semi-supervised deep learning for breast ultrasound computer-aided diagnosis
Erlei Zhang, Stephen Seiler, Mingli Chen, et al.
Physics in Medicine and Biology (2020) Vol. 65, Iss. 12, pp. 125005-125005
Open Access | Times Cited: 33
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