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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 state of the art for artificial intelligence in lung digital pathology
Vidya Sankar Viswanathan, Paula Toro, Germán Corredor, et al.
The Journal of Pathology (2022) Vol. 257, Iss. 4, pp. 413-429
Open Access | Times Cited: 62

Showing 1-25 of 62 citing articles:

Explainability and causability in digital pathology
Markus Plass, Michaela Kargl, Tim‐Rasmus Kiehl, et al.
The Journal of Pathology Clinical Research (2023) Vol. 9, Iss. 4, pp. 251-260
Open Access | Times Cited: 45
Computational pathology in cancer diagnosis, prognosis, and prediction – present day and prospects
Gregory Verghese, Jochen K. Lennerz, Danny Ruta, et al.
The Journal of Pathology (2023) Vol. 260, Iss. 5, pp. 551-563
Open Access | Times Cited: 33
Unraveling the potential of 3D bioprinted immunomodulatory materials for regulating macrophage polarization: State-of-the-art in bone and associated tissue regeneration
Sayan Deb Dutta, Tejal V. Patil, Keya Ganguly, et al.
Bioactive Materials (2023) Vol. 28, pp. 284-310
Open Access | Times Cited: 27
Artificial intelligence in digital histopathology for predicting patient prognosis and treatment efficacy in breast cancer
Christine McCaffrey, Chowdhury Arif Jahangir, Clodagh Murphy, et al.
Expert Review of Molecular Diagnostics (2024) Vol. 24, Iss. 5, pp. 363-377
Open Access | Times Cited: 11
Enhancing early lung cancer detection with MobileNet: A comprehensive transfer learning approach
Raquel Ochoa-Ornelas, Alberto Gudiño-Ochoa, J A García-Rodríguez, et al.
Franklin Open (2025), pp. 100222-100222
Open Access | Times Cited: 1
Statistical analysis of spatial patterns in tumor microenvironment images
Mohamed M. Benimam, Vannary Meas‐Yedid, Suvadip Mukherjee, et al.
Nature Communications (2025) Vol. 16, Iss. 1
Open Access | Times Cited: 1
Why do errors arise in artificial intelligence diagnostic tools in histopathology and how can we minimize them?
H Evans, David Snead
Histopathology (2023) Vol. 84, Iss. 2, pp. 279-287
Open Access | Times Cited: 20
Unleashing the potential of AI for pathology: challenges and recommendations
Amina Asif, Kashif Rajpoot, Simon Graham, et al.
The Journal of Pathology (2023) Vol. 260, Iss. 5, pp. 564-577
Open Access | Times Cited: 17
Advanced 3D In Vitro Lung Fibrosis Models: Contemporary Status, Clinical Uptake, and Prospective Outlooks
Nipun Jain, Bharat Bhushan, M. Natarajan, et al.
ACS Biomaterials Science & Engineering (2024) Vol. 10, Iss. 3, pp. 1235-1261
Closed Access | Times Cited: 7
Pathomic Features Reveal Immune and Molecular Evolution From Lung Preneoplasia to Invasive Adenocarcinoma
Pingjun Chen, Frank Rojas, Xin Hu, et al.
Modern Pathology (2023) Vol. 36, Iss. 12, pp. 100326-100326
Open Access | Times Cited: 15
Application of machine learning based genome sequence analysis in pathogen identification
Yunqiu Gao, Min Liu
Frontiers in Microbiology (2024) Vol. 15
Open Access | Times Cited: 5
Predicting peritoneal recurrence in gastric cancer with serosal invasion using a pathomics nomogram
Dexin Chen, Jianbo Lai, Jiaxin Cheng, et al.
iScience (2023) Vol. 26, Iss. 3, pp. 106246-106246
Open Access | Times Cited: 12
A Review of AI-Based Radiomics and Computational Pathology Approaches in Triple-Negative Breast Cancer: Current Applications and Perspectives
Germán Corredor, Satvika Bharadwaj, Tilak Pathak, et al.
Clinical Breast Cancer (2023) Vol. 23, Iss. 8, pp. 800-812
Open Access | Times Cited: 12
See Lung Cancer with an AI
Joanna Bidzińska, Edyta Szurowska
Cancers (2023) Vol. 15, Iss. 4, pp. 1321-1321
Open Access | Times Cited: 11
The Artificial Intelligence in Teledermatology: A Narrative Review on Opportunities, Perspectives, and Bottlenecks
Daniele Giansanti
International Journal of Environmental Research and Public Health (2023) Vol. 20, Iss. 10, pp. 5810-5810
Open Access | Times Cited: 11
Quantifying Intratumoral Heterogeneity and Immunoarchitecture Generated In-Silico by a Spatial Quantitative Systems Pharmacology Model
Mehdi Nikfar, Hao‐Yang Mi, Chang Gong, et al.
Cancers (2023) Vol. 15, Iss. 10, pp. 2750-2750
Open Access | Times Cited: 11
Deciphering Lung Adenocarcinoma Progression Through Molecular Insights: The Challenges and Potential of Radiomics and Machine Learning
Ritu R. Gill, Despina Kontos
Journal of Thoracic Oncology (2025) Vol. 20, Iss. 1, pp. 20-22
Closed Access
Application of Artificial Intelligence in Radiological Image Analysis for Pulmonary Disease Diagnosis: A Review of Current Methods and Challenges
Karolina Zalewa, Joanna Olszak, Wojciech Kapłan, et al.
Journal of Education Health and Sport (2025) Vol. 77, pp. 56893-56893
Open Access
Deep learning based analysis of G3BP1 protein expression to predict the prognosis of nasopharyngeal carcinoma
Linshan Zhou, Mu Yang, Jiadi Luo, et al.
PLoS ONE (2025) Vol. 20, Iss. 1, pp. e0315893-e0315893
Open Access
Artificial intelligence for diagnosis and predictive biomarkers in Non-Small cell lung cancer Patients: New promises but also new hurdles for the pathologist
Paul Hofman, Iordanis Ourailidis, Eva Romanovsky, et al.
Lung Cancer (2025) Vol. 200, pp. 108110-108110
Closed Access
RMD-Net: A Deep Learning Framework for Automated IHC Scoring of Lung Cancer IL-24
Zihao He, Dongyao Jia, Yinan Shi, et al.
Mathematics (2025) Vol. 13, Iss. 3, pp. 417-417
Open Access
Multimodal radiopathological integration for prognosis and prediction of adjuvant chemotherapy benefit in resectable lung adenocarcinoma: a multicentre study
Huan Lin, Junjie Hua, Zhengze Gong, et al.
Cancer Letters (2025) Vol. 616, pp. 217557-217557
Closed Access
Advanced Techniques for Cancer Research with Multimodal Fusion and Deep Learning
Mallikarjun Shankar, Lekshmi Kalinathan, J. Senthil Murugan
Communications in computer and information science (2025), pp. 243-251
Closed Access
Comparative performance of PD‐L1 scoring by pathologists and AI algorithms
Markus Plass, G. Olteanu, Sanja Đačić, et al.
Histopathology (2025)
Open Access
Construction of a risk screening and visualization system for pulmonary nodule in physical examination population based on feature self-recognition machine learning model
Tian Fang, Yongchun Lin, Liming Wang, et al.
Frontiers in Medicine (2025) Vol. 11
Open Access
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