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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:

Radiomics and artificial intelligence in breast imaging: a survey
Tianyu Zhang, Tao Tan, Riccardo Samperna, et al.
Artificial Intelligence Review (2023) Vol. 56, Iss. S1, pp. 857-892
Closed Access | Times Cited: 19

Showing 19 citing articles:

How Artificial Intelligence Is Shaping Medical Imaging Technology: A Survey of Innovations and Applications
Luís Coelho
Bioengineering (2023) Vol. 10, Iss. 12, pp. 1435-1435
Open Access | Times Cited: 137
Diagnostic capabilities of artificial intelligence as an additional reader in a breast cancer screening program
Mustafa Ege Şeker, Yılmaz Onat Köylüoğlu, Ayşe Özaydın, et al.
European Radiology (2024) Vol. 34, Iss. 9, pp. 6145-6157
Open Access | Times Cited: 8
IMPORTANT-Net: Integrated MRI multi-parametric increment fusion generator with attention network for synthesizing absent data
Tianyu Zhang, Tao Tan, Luyi Han, et al.
Information Fusion (2024) Vol. 108, pp. 102381-102381
Open Access | Times Cited: 8
Quantum computational infusion in extreme learning machines for early multi-cancer detection
Anas Bilal, Muhammad Shafiq, Waeal J. Obidallah, et al.
Journal Of Big Data (2025) Vol. 12, Iss. 1
Open Access
Optimizing BI-RADS 4 Lesion Assessment Using Lightweight Convolutional Neural Network with CBAM in Contrast Enhanced Mammography
Oladosu Oyebisi Oladimeji, Hamail Ayaz, Ian McLoughlin, et al.
Lecture notes in computer science (2025), pp. 96-106
Closed Access
Graph Neural Networks for Modelling Breast Biomechanical Compression
Hadeel Awwad, Eloy García, Robert Martí
Lecture notes in computer science (2025), pp. 169-180
Closed Access
One for All: UNET Training on Single-Sequence Masks for Multi-sequence Breast MRI Segmentation
Jarek M. van Dijk, Luyi Han, Luuk Balkenende, et al.
Lecture notes in computer science (2025), pp. 32-41
Closed Access
Multimodal Breast MRI Language-Image Pretraining (MLIP): An Exploration of a Breast MRI Foundation Model
Nika Rasoolzadeh, Tianyu Zhang, Yuan Gao, et al.
Lecture notes in computer science (2025), pp. 42-53
Closed Access
MRI Breast Tissue Segmentation Using nnU-Net for Biomechanical Modeling
Melika Pooyan, Hadeel Awwad, Eloy García, et al.
Lecture notes in computer science (2025), pp. 191-201
Closed 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
Predicting axillary response to neoadjuvant chemotherapy using peritumoral and intratumoral ultrasound radiomics in breast cancer molecular subtypes
Jiejie Yao, Xiaohong Jia, Wei Zhou, et al.
iScience (2024) Vol. 27, Iss. 9, pp. 110716-110716
Open Access | Times Cited: 4
Technical Review of Breast Cancer Screening and Detection using Artificial Intelligence and Radiomics
Arshpreet Singh, Simranpreet Kaur, Deepjyot Singh, et al.
2022 9th International Conference on Computing for Sustainable Global Development (INDIACom) (2024), pp. 1171-1176
Closed Access | Times Cited: 2
Contrast-enhanced mammography: better with AI?
Tianyu Zhang, Ritse M. Mann
European Radiology (2023) Vol. 34, Iss. 2, pp. 914-916
Closed Access | Times Cited: 4
Machine learning in healthcare strategic management: a systematic literature review
Sand Mohammad Salhout
Arab Gulf Journal of Scientific Research (2023) Vol. 42, Iss. 4, pp. 1530-1554
Open Access | Times Cited: 4
Explainable breast cancer molecular expression prediction using multi-task deep-learning based on 3D whole breast ultrasound
Zengan Huang, Xin Zhang, Yan Ju, et al.
Insights into Imaging (2024) Vol. 15, Iss. 1
Open Access
An explainable longitudinal multi-modal fusion model for predicting neoadjuvant therapy response in women with breast cancer
Yuan Gao, Sofía Ventura‐Díaz, Xin Wang, et al.
Nature Communications (2024) Vol. 15, Iss. 1
Open Access
Feature Imitating Networks Enhance the Performance, Reliability and Speed of Deep Learning on Biomedical Image Processing Tasks
Shangyang Min, Hassan Bagher Ebadian, Tuka Alhanai, et al.
(2024), pp. 1-5
Open Access
Machine learning can reliably predict malignancy of breast lesions based on clinical and ultrasonographic features
Isabela Buzatto, Sarah Abud Recife, L. Silva Miguel, et al.
Breast Cancer Research and Treatment (2024)
Closed Access
Predicting axillary lymph node metastasis in breast cancer using a multimodal radiomics and deep learning model
Fuyu Guo, Shiwei Sun, Xiaoqian Deng, et al.
Frontiers in Immunology (2024) Vol. 15
Open Access
SVM in Classification of stage 0~II and III~IV with Breast Cancer : A Retrospective Cohort Study on a bicentric cohort
Yeang Guo, Tao Tan, Ronglin Ronglin, et al.
(2023), pp. 1-10
Closed Access
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