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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 review of the machine learning datasets in mammography, their adherence to the FAIR principles and the outlook for the future
Joe Logan, Paul Kennedy, Daniel Catchpoole
Scientific Data (2023) Vol. 10, Iss. 1
Open Access | Times Cited: 16

Showing 16 citing articles:

Deep Learning in Breast Cancer Imaging: State of the Art and Recent Advancements in Early 2024
Alessandro Carriero, Léon Groenhoff, Elizaveta Vologina, et al.
Diagnostics (2024) Vol. 14, Iss. 8, pp. 848-848
Open Access | Times Cited: 21
An Enhanced LightGBM-Based Breast Cancer Detection Technique Using Mammography Images
Abdul Rahaman Wahab Sait, R. Nagaraj
Diagnostics (2024) Vol. 14, Iss. 2, pp. 227-227
Open Access | Times Cited: 4
Towards an EU Charter of Digital Patients’ Rights in the Age of Artificial Intelligence
Hannah van Kolfschooten
Deleted Journal (2025) Vol. 4, Iss. 1
Open Access
Prospects for the Application of Artificial Intelligence in Mammography
Siuzanna F. Saibu
Journal of radiology and nuclear medicine (2025) Vol. 105, Iss. 5, pp. 282-286
Open Access
Diversity, inclusivity and traceability of mammography datasets used in development of Artificial Intelligence technologies: a systematic review
Elinor Laws, Joanne Palmer, Joseph Alderman, et al.
Clinical Imaging (2024) Vol. 118, pp. 110369-110369
Open Access | Times Cited: 3
Comparative Study of Artificial Intelligence Models for Breast Cancer Detection
Tanvi Meet Dhruv
Journal of Trends in Computer Science and Smart Technology (2024) Vol. 6, Iss. 1, pp. 18-36
Open Access | Times Cited: 1
Machine learning data practices through a data curation lens: An evaluation framework
Eshta Bhardwaj, Harshit Gujral, Siyi Wu, et al.
2022 ACM Conference on Fairness, Accountability, and Transparency (2024) Vol. 31, pp. 1055-1067
Open Access | Times Cited: 1
Challenges in Implementing Artificial Intelligence in Breast Cancer Screening Programs: A Systematic Review and Framework for Safe Adoption (Preprint)
Serene Si Ning Goh, Rachel Sze Jen Goh, Bryan Chong, et al.
Journal of Medical Internet Research (2024)
Open Access | Times Cited: 1
A Systematic Literature Review on Mammography: Deep Learning in Redefining Breast Cancer Diagnosis for the Asian Perspective
Ashwini Amin, U. Dinesh Acharya, P. C. Siddalingaswamy, et al.
Research Square (Research Square) (2024)
Open Access
Breast Mass Detection and Classification using Machine Learning approaches on 2 D Mammogram: A Comprehensive Review
N. Shankari, Vidya Kudva, Roopa B. Hegde
Critical Reviews in Biomedical Engineering (2024) Vol. 52, Iss. 4, pp. 41-60
Closed Access
Transparency in Computer-Aided Breast Cancer Diagnosis Tool Development: A CBIS-DDSM Case Study
Ling Liao, Eva Aagaard
Research Square (Research Square) (2024)
Open Access
Systematic Review of Challenges in Implementing Artificial Intelligence in Breast Cancer Screening Programs: Towards a Framework for Safe Adoption (Preprint)
Serene Si Ning Goh, Rachel Sze Jen Goh, Bryan Chong, et al.
(2024)
Open Access
Data Domain Adaptation in Federated Learning in the Breast Mammography Image Classification Problem
Łukasz Erimus, Aleksandra Borowska, Adrian Jaromin, et al.
(2024), pp. 1-6
Closed Access
Modified Dense Convolution Neural Network (md-cnn) for Breast Cancer Detection Using Mammography Images
Sugandha Gupta, Susmita Ray, Ashish Khanna
Lecture notes in networks and systems (2024), pp. 635-645
Closed Access
An open codebase for enhancing transparency in deep learning-based breast cancer diagnosis utilizing CBIS-DDSM data
Ling Liao, Eva Aagaard
Scientific Reports (2024) Vol. 14, Iss. 1
Open Access
Deep Learning Based Breast Cancer Detection Using Decision Fusion
Doğu Manalı, Hasan Demirel, Alaa Eleyan
Computers (2024) Vol. 13, Iss. 11, pp. 294-294
Open Access
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