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:

Accelerating histopathology workflows with generative AI-based virtually multiplexed tumour profiling
Pushpak Pati, Sofia Karkampouna, Francesco Bonollo, et al.
Nature Machine Intelligence (2024) Vol. 6, Iss. 9, pp. 1077-1093
Open Access | Times Cited: 8

Showing 8 citing articles:

Current Advancements in Digital Neuropathology and Machine Learning for the Study of Neurodegenerative Diseases
Dana R. Julian, Afshin Bahramy, M. Pinson Neal, et al.
American Journal Of Pathology (2025)
Open Access

Single-Cell Multi-Omics: Insights into Therapeutic Innovations to Advance Treatment in Cancer
Ai-xing Guan, Camelia Quek
International Journal of Molecular Sciences (2025) Vol. 26, Iss. 6, pp. 2447-2447
Open Access

Virtual Staining for Pathology: Challenges, Limitations and Perspectives
Weiping Lin, Yihuang Hu, Rong Zhu, et al.
(2025)
Closed Access

Artificial Intelligence-Based Virtual Staining Platform for Identifying Tumor-Associated Macrophages from Hematoxylin and Eosin-Stained Images
Arpit Aggarwal, Mayukhmala Jana, Amritpal Singh, et al.
European Journal of Cancer (2025), pp. 115390-115390
Open Access

Multi-V-Stain: Multiplexed Virtual Staining of Histopathology Whole-Slide Images
Sonali Andani, Boqi Chen, Joanna Ficek-Pascual, et al.
medRxiv (Cold Spring Harbor Laboratory) (2024)
Open Access | Times Cited: 2

Machine learning methods for histopathological image analysis: Updates in 2024
Daisuke Komura, Mieko Ochi, Shumpei Ishikawa
Computational and Structural Biotechnology Journal (2024) Vol. 27, pp. 383-400
Open Access

Deep Learning Predicts Subtype Heterogeneity and Outcomes in Luminal A Breast Cancer Using Routinely Stained Whole Slide Images
Nikhil Cherian Kurian, Peter H. Gann, Neeraj Kumar, et al.
Cancer Research Communications (2024)
Open Access

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