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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:

Predicting the molecular subtype of breast cancer and identifying interpretable imaging features using machine learning algorithms
Mengwei Ma, Renyi Liu, Chanjuan Wen, et al.
European Radiology (2021) Vol. 32, Iss. 3, pp. 1652-1662
Closed Access | Times Cited: 74

Showing 1-25 of 74 citing articles:

Application of serum SERS technology based on thermally annealed silver nanoparticle composite substrate in breast cancer
Zhiyuan Cheng, Hongyi Li, Chen Chen, et al.
Photodiagnosis and Photodynamic Therapy (2023) Vol. 41, pp. 103284-103284
Closed Access | Times Cited: 54
Artificial Intelligence for Clinical Prediction: Exploring Key Domains and Essential Functions
Mohamed Khalifa, Mona Albadawy
Computer Methods and Programs in Biomedicine Update (2024) Vol. 5, pp. 100148-100148
Open Access | Times Cited: 37
On the failings of Shapley values for explainability
Xuanxiang Huang, João Marques‐Silva
International Journal of Approximate Reasoning (2024) Vol. 171, pp. 109112-109112
Closed Access | Times Cited: 25
Machine learning-based models for the prediction of breast cancer recurrence risk
Duo Zuo, Lexin Yang, Yu Jin, et al.
BMC Medical Informatics and Decision Making (2023) Vol. 23, Iss. 1
Open Access | Times Cited: 34
Radiogenomic analysis of prediction HER2 status in breast cancer by linking ultrasound radiomic feature module with biological functions
Hao Cui, Yue Sun, Dantong Zhao, et al.
Journal of Translational Medicine (2023) Vol. 21, Iss. 1
Open Access | Times Cited: 24
Artificial intelligence: opportunities and challenges in the clinical applications of triple-negative breast cancer
Jiamin Guo, Junjie Hu, Yichen Zheng, et al.
British Journal of Cancer (2023) Vol. 128, Iss. 12, pp. 2141-2149
Closed Access | Times Cited: 22
Fuzzy inference system with interpretable fuzzy rules: Advancing explainable artificial intelligence for disease diagnosis—A comprehensive review
Jin Cao, Zhou Ta, Shaohua Zhi, et al.
Information Sciences (2024) Vol. 662, pp. 120212-120212
Open Access | Times Cited: 11
Multiparametric MRI model to predict molecular subtypes of breast cancer using Shapley additive explanations interpretability analysis
Yao Huang, Xiaoxia Wang, Ying Cao, et al.
Diagnostic and Interventional Imaging (2024) Vol. 105, Iss. 5, pp. 191-205
Closed Access | Times Cited: 8
MOB-CBAM: A dual-channel attention-based deep learning generalizable model for breast cancer molecular subtypes prediction using mammograms
Iqra Nissar, Shahzad Alam, Sarfaraz Masood, et al.
Computer Methods and Programs in Biomedicine (2024) Vol. 248, pp. 108121-108121
Closed Access | Times Cited: 8
Advancing precision medicine: the transformative role of artificial intelligence in immunogenomics, radiomics, and pathomics for biomarker discovery and immunotherapy optimization
Luchen Chang, Jiamei Liu, Jialin Zhu, et al.
Cancer Biology and Medicine (2025), pp. 1-15
Open Access | Times Cited: 1
Prediction of pulmonary embolism by an explainable machine learning approach in the real world
Qiao Zhou, Ruichen Huang, Xingyu Xiong, et al.
Scientific Reports (2025) Vol. 15, Iss. 1
Open Access | Times Cited: 1
Utilizing Feature Selection Techniques for AI-Driven Tumor Subtype Classification: Enhancing Precision in Cancer Diagnostics
Jihan Wang, Zhengxiang Zhang, Yangyang Wang
Biomolecules (2025) Vol. 15, Iss. 1, pp. 81-81
Open Access | Times Cited: 1
Artificial Intelligence in Breast Ultrasound: From Diagnosis to Prognosis—A Rapid Review
Nicole Brunetti, Massimo Calabrese, Carlo Martinoli, et al.
Diagnostics (2022) Vol. 13, Iss. 1, pp. 58-58
Open Access | Times Cited: 29
A scoping review of interpretability and explainability concerning artificial intelligence methods in medical imaging
Mélanie Champendal, Henning Müller, John O. Prior, et al.
European Journal of Radiology (2023) Vol. 169, pp. 111159-111159
Open Access | Times Cited: 17
Immune, metabolic landscapes of prognostic signatures for lung adenocarcinoma based on a novel deep learning framework
Shimei Qin, Shibin Sun, Yahui Wang, et al.
Scientific Reports (2024) Vol. 14, Iss. 1
Open Access | Times Cited: 6
Artificial intelligence in oncologic imaging
Melissa Chen, Admir Terzić, Anton S. Becker, et al.
European Journal of Radiology Open (2022) Vol. 9, pp. 100441-100441
Open Access | Times Cited: 24
Artificial intelligence in breast imaging: Current situation and clinical challenges
Chao You, Yiyuan Shen, Shiyun Sun, et al.
Exploration (2023) Vol. 3, Iss. 5
Open Access | Times Cited: 13
The Emergence of the Potential Therapeutic Targets: Ultrasound-Based Radiomics in the Prediction of Human Epidermal Growth Factor Receptor 2-Low Breast Cancer
Yu Du, Fang Li, Manqi Zhang, et al.
Academic Radiology (2024) Vol. 31, Iss. 7, pp. 2674-2683
Closed Access | Times Cited: 5
Diagnostic performance of ultrasound-based artificial intelligence for predicting key molecular markers in breast cancer: A systematic review and meta-analysis
Y. Fu, Jialin Zhou, Junfeng Li
PLoS ONE (2024) Vol. 19, Iss. 5, pp. e0303669-e0303669
Open Access | Times Cited: 4
Paving the Roadmap for XAI and IML in Healthcare: Data-Driven Discoveries and the FIXAIH Framework
Saeed M. Alghamdi, Rashid Mehmood, Fahad Alqurashi, et al.
(2025)
Closed Access
Development and validation of an ultrasound-based interpretable machine learning model for the classification of ≤3 cm hepatocellular carcinoma: a multicentre retrospective diagnostic study
Zhicheng Du, Fangying Fan, Jun Ma, et al.
EClinicalMedicine (2025) Vol. 81, pp. 103098-103098
Closed Access
Harnessing Artificial Intelligence for Precision Diagnosis and Treatment of Triple Negative Breast Cancer
Md Sadique Hussain, Prasanna Srinivasan Ramalingam, Gayathri Chellasamy, et al.
Clinical Breast Cancer (2025)
Closed Access
Transparency and Representation in Clinical Research Utilizing Artificial Intelligence in Oncology: A Scoping Review
Anjali D'Amiano, Tia Cheunkarndee, Chinenye C. Azoba, et al.
Cancer Medicine (2025) Vol. 14, Iss. 5
Open Access
Application of deep learning on automated breast ultrasound: Current developments, challenges, and opportunities
Ruixin Wang, Zhiyuan Wang, Yuanming Xiao, et al.
Meta-Radiology (2025), pp. 100138-100138
Open Access
Enhancing Diagnostic Efficiency: A Radiomics Approach for Distinguishing Benign and Malignant Breast Lesions Using BI-RADS Features from Ultrasound Imaging
Runqiu Cai, Man Wang, Yan Yu, et al.
Clinical Breast Cancer (2025)
Closed Access
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