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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:

Oncotype DX Breast Recurrence Score®: A Review of its Use in Early-Stage Breast Cancer
Yahiya Y. Syed
Molecular Diagnosis & Therapy (2020) Vol. 24, Iss. 5, pp. 621-632
Closed Access | Times Cited: 53

Showing 1-25 of 53 citing articles:

Molecular Biomarkers in Cancer
Virinder Kaur Sarhadi, Gemma Armengol
Biomolecules (2022) Vol. 12, Iss. 8, pp. 1021-1021
Open Access | Times Cited: 270
Breast cancer, screening and diagnostic tools: All you need to know
Diego Barba, Ariana León-Sosa, Paulina Lugo, et al.
Critical Reviews in Oncology/Hematology (2020) Vol. 157, pp. 103174-103174
Open Access | Times Cited: 104
Leveraging transcriptomics for precision diagnosis: Lessons learned from cancer and sepsis
Maria Tsakiroglou, A.G. Evans, Munir Pirmohamed
Frontiers in Genetics (2023) Vol. 14
Open Access | Times Cited: 25
The biological and technical challenges facing utilizing circulating tumor DNA in non-metastatic breast cancer patients
Zihang Zeng, Zongbi Yi, Binghe Xu
Cancer Letters (2025) Vol. 616, pp. 217574-217574
Closed Access | Times Cited: 1
Ultrasound-Based Radiomics Analysis for Predicting Disease-Free Survival of Invasive Breast Cancer
Lang Xiong, Haolin Chen, Xiaofeng Tang, et al.
Frontiers in Oncology (2021) Vol. 11
Open Access | Times Cited: 48
Omics Technologies Improving Breast Cancer Research and Diagnostics
Arianna Orsini, Chiara Diquigiovanni, Elena Bonora
International Journal of Molecular Sciences (2023) Vol. 24, Iss. 16, pp. 12690-12690
Open Access | Times Cited: 18
Prediction of Disease-Free Survival in Breast Cancer using Deep Learning with Ultrasound and Mammography: A Multicenter Study
Junqi Han, Hui Hua, Fei Jie, et al.
Clinical Breast Cancer (2024) Vol. 24, Iss. 3, pp. 215-226
Closed Access | Times Cited: 7
MRI Radiomics and Machine Learning for the Prediction of Oncotype Dx Recurrence Score in Invasive Breast Cancer
Valeria Romeo, Renato Cuocolo, Luca Sanduzzi, et al.
Cancers (2023) Vol. 15, Iss. 6, pp. 1840-1840
Open Access | Times Cited: 13
Molecular Changes in Breast Cancer Induced by Radiation Therapy
Kim Sheva, Sangita Roy Chowdhury, Nataly Kravchenko‐Balasha, et al.
International Journal of Radiation Oncology*Biology*Physics (2024) Vol. 120, Iss. 2, pp. 465-481
Closed Access | Times Cited: 5
Applying a GAN-based classifier to improve transcriptome-based prognostication in breast cancer
Cristiano Guttà, Christoph Morhard, Markus Rehm
PLoS Computational Biology (2023) Vol. 19, Iss. 4, pp. e1011035-e1011035
Open Access | Times Cited: 12
Genetic Testing Enhances the Precision Diagnosis and Treatment of Breast Cancer
Ting-Lin Yang, Wenhui Li, Tao Huang, et al.
International Journal of Molecular Sciences (2023) Vol. 24, Iss. 23, pp. 16607-16607
Open Access | Times Cited: 11
Digital profiling of gene expression from histology images with linearized attention
Marija Pizurica, Yuanning Zheng, Francisco Carrillo‐Pérez, et al.
Nature Communications (2024) Vol. 15, Iss. 1
Open Access | Times Cited: 4
MRI biomarkers and their correlation with the Oncotype DX test
A. Aranaz Murillo, S. Cruz Círia, A. García Barrado, et al.
Radiología (English Edition) (2025) Vol. 67, Iss. 1, pp. 54-60
Closed Access
Exploring the Potential of Adjuvant CDK4/6 Inhibitors in Hormone Receptor-Positive Early Breast Cancer: A Consistent Approach for All
Jianbin Li
Cancers (2025) Vol. 17, Iss. 4, pp. 561-561
Open Access
Blood-Based mRNA Tests as Emerging Diagnostic Tools for Personalised Medicine in Breast Cancer
Helena Čelešnik, Uroš Potočnik
Cancers (2023) Vol. 15, Iss. 4, pp. 1087-1087
Open Access | Times Cited: 10
Identification of Patients with Early HR+ HER2− Breast Cancer at High Risk of Recurrence
Peter A. Fasching, Hans Kreipe, Lucia Del Mastro, et al.
Geburtshilfe und Frauenheilkunde (2024) Vol. 84, Iss. 02, pp. 164-184
Open Access | Times Cited: 3
Software BreastAnalyser for the semi-automatic analysis of breast cancer immunohistochemical images
Marina Rodríguez-Candela Mateos, Maria Azmat, Paz Santiago-Freijanes, et al.
Scientific Reports (2024) Vol. 14, Iss. 1
Open Access | Times Cited: 3
Gold Nanobiosensors: Pioneering Breakthroughs in Precision Breast Cancer Detection
Soheil Sadr, Ashkan Hajjafari, Abbas Rahdar, et al.
European Journal of Medicinal Chemistry Reports (2024), pp. 100238-100238
Open Access | Times Cited: 3
Deep pathomics: A new image-based tool for predicting response to treatment in stage III non-small cell lung cancer
Lorenzo Nibid, Carlo Greco, Ermanno Cordelli, et al.
PLoS ONE (2023) Vol. 18, Iss. 11, pp. e0294259-e0294259
Open Access | Times Cited: 7
Anatomy Versus Biology: What Guides Chemotherapy Decisions in Older Patients With Breast Cancer?
Sydney M. Record, Samantha M. Thomas, William M. Tian, et al.
Journal of Surgical Research (2024) Vol. 296, pp. 654-664
Closed Access | Times Cited: 2
Tumor grade and progesterone receptor status in predicting benefit of chemotherapy in high genomic risk breast cancer
Ke Liu, Guiping Chen, Xueqin Chen, et al.
Expert Review of Anticancer Therapy (2024) Vol. 24, Iss. 10, pp. 1021-1028
Closed Access | Times Cited: 2
Discovering Explainable Biomarkers for Breast Cancer Anti-PD1 Response via Network Shapley Value Analysis
Chenxi Sun, Zhi‐Ping Liu
Computer Methods and Programs in Biomedicine (2024) Vol. 257, pp. 108481-108481
Closed Access | Times Cited: 2
Drug Metabolism for the Identification of Clinical Biomarkers in Breast Cancer
Bárbara Costa, Nuno Vale
International Journal of Molecular Sciences (2022) Vol. 23, Iss. 6, pp. 3181-3181
Open Access | Times Cited: 11
Xerna™ TME Panel is a machine learning-based transcriptomic biomarker designed to predict therapeutic response in multiple cancers
Mark Uhlik, Daniel Pointing, Seema Iyer, et al.
Frontiers in Oncology (2023) Vol. 13
Open Access | Times Cited: 6
Genomic biomarkers: Unveiling the potential for precise cancer therapy response
Gurjeet Kaur, Paras Pahwa, Ajay Prakash, et al.
Indian Journal of Pharmacology (2023) Vol. 55, Iss. 4, pp. 213-215
Open Access | Times Cited: 5
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