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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:

The potential of artificial intelligence-based applications in kidney pathology
Roman D. Büllow, Jon N. Marsh, S. Joshua Swamidass, et al.
Current Opinion in Nephrology & Hypertension (2022) Vol. 31, Iss. 3, pp. 251-257
Open Access | Times Cited: 13

Showing 13 citing articles:

Operational greenhouse-gas emissions of deep learning in digital pathology: a modelling study
Alireza Vafaei Sadr, Roman D. Bülow, Saskia von Stillfried, et al.
The Lancet Digital Health (2023) Vol. 6, Iss. 1, pp. e58-e69
Open Access | Times Cited: 16
Challenges in standardizing preimplantation kidney biopsy assessments and the potential of AI-Driven solutions
Karolien Wellekens, Priyanka Koshy, Maarten Naesens
Current Opinion in Nephrology & Hypertension (2025)
Closed Access
Time for a full digital approach in nephropathology: a systematic review of current artificial intelligence applications and future directions
Giorgio Cazzaniga, Mattia Rossi, Albino Eccher, et al.
Journal of Nephrology (2023) Vol. 37, Iss. 1, pp. 65-76
Open Access | Times Cited: 12
A new, deep learning–based method for the analysis of autopsy kidney samples used to study sex differences in glomerular density and size in a forensic population
Valérie Vilmont, Nadine Ngatchou, Ghislaine Lioux, et al.
International Journal of Legal Medicine (2024) Vol. 138, Iss. 3, pp. 873-882
Open Access | Times Cited: 2
The Cross-Scale Association between Pathomics and Radiomics Features in Immunotherapy-Treated NSCLC Patients: A Preliminary Study
Abdou Khadir Dia, Leyla Ebrahimpour, Sevinj Yolchuyeva, et al.
Cancers (2024) Vol. 16, Iss. 2, pp. 348-348
Open Access | Times Cited: 2
Kidney medicine meets computer vision: a bibliometric analysis
Junren Chen, Rui Chen, Liangyin Chen, et al.
International Urology and Nephrology (2024) Vol. 56, Iss. 10, pp. 3361-3380
Closed Access | Times Cited: 2
Banff Digital Pathology Working Group: Image Bank, Artificial Intelligence Algorithm, and Challenge Trial Developments
Alton B. Farris, Mariam P. Alexander, Ulysses J. Balis, et al.
Transplant International (2023) Vol. 36
Open Access | Times Cited: 5
A Spatially Guided Machine-Learning Method to Classify and Quantify Glomerular Patterns of Injury in Histology Images
Justinas Besusparis, Mindaugas Morkūnas, Arvydas Laurinavičius
Journal of Imaging (2023) Vol. 9, Iss. 10, pp. 220-220
Open Access | Times Cited: 2
Automated quantification and statistical assessment of proliferating cardiomyocyte rates in embryonic hearts
Julius Bogomolovas, Zengming Zhang, Tongbin Wu, et al.
AJP Heart and Circulatory Physiology (2022) Vol. 324, Iss. 3, pp. H288-H292
Open Access | Times Cited: 3
Unsupervised learning for labeling global glomerulosclerosis
Hrafn Weishaupt, Justinas Besusparis, Cleo‐Aron Weis, et al.
bioRxiv (Cold Spring Harbor Laboratory) (2024)
Open Access
Synthetic data as an investigative tool in hypertension and renal diseases research
Aleena Jamal, Som Singh, Fawad Qureshi
World Journal of Methodology (2024) Vol. 15, Iss. 1
Closed Access
Ecologically sustainable benchmarking of AI models for histopathology
Yu-Chia Lan, Martin Strauch, Pourya Pilva, et al.
npj Digital Medicine (2024) Vol. 7, Iss. 1
Open Access
Machine Learning Illuminates the Extraglomerular Microvasculature
Vanderlene L. Kung, Jonathan W. Nelson
Kidney360 (2023) Vol. 4, Iss. 5, pp. 578-579
Open Access
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