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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:

Automated histological classification for digital pathology images of colonoscopy specimen via deep learning
Sun‐ju Byeon, Jungkap Park, Yoon Ah Cho, et al.
Scientific Reports (2022) Vol. 12, Iss. 1
Open Access | Times Cited: 30

Showing 1-25 of 30 citing articles:

On the Analyses of Medical Images Using Traditional Machine Learning Techniques and Convolutional Neural Networks
Saeed Iqbal, Adnan N. Qureshi, Jianqiang Li, et al.
Archives of Computational Methods in Engineering (2023) Vol. 30, Iss. 5, pp. 3173-3233
Open Access | Times Cited: 84
Application of artificial intelligence in diagnosis and treatment of colorectal cancer: A novel Prospect
Zugang Yin, Chenhui Yao, Limin Zhang, et al.
Frontiers in Medicine (2023) Vol. 10
Open Access | Times Cited: 44
AI in Pathology: What could possibly go wrong?
Keisuke Nakagawa, Lama Moukheiber, Leo Anthony Celi, et al.
Seminars in Diagnostic Pathology (2023) Vol. 40, Iss. 2, pp. 100-108
Closed Access | Times Cited: 41
Breast cancer histopathology image-based gene expression prediction using spatial transcriptomics data and deep learning
Md Mamunur Rahaman, Ewan K.A. Millar, Erik Meijering
Scientific Reports (2023) Vol. 13, Iss. 1
Open Access | Times Cited: 19
Improving performance in colorectal cancer histology decomposition using deep and ensemble machine learning
Fabi Prezja, Leevi Annala, Sampsa Kiiskinen, et al.
Heliyon (2024) Vol. 10, Iss. 18, pp. e37561-e37561
Open Access | Times Cited: 7
Improved classification of colorectal polyps on histopathological images with ensemble learning and stain normalization
Sena Busra Yengec-Tasdemir, Zafer Aydın, Ebru Akay, et al.
Computer Methods and Programs in Biomedicine (2023) Vol. 232, pp. 107441-107441
Closed Access | Times Cited: 15
Advancing Artificial Intelligence Integration Into the Pathology Workflow: Exploring Opportunities in Gastrointestinal Tract Biopsies
Fazilet Yilmaz, Arlen Brickman, Fedaa Najdawi, et al.
Laboratory Investigation (2024) Vol. 104, Iss. 5, pp. 102043-102043
Closed Access | Times Cited: 4
Spatial Integration of Multi-Omics Data using the novel Multi-Omics Imaging Integration Toolset
Maximillian Wess, Maria Andersen, Elise Midtbust, et al.
bioRxiv (Cold Spring Harbor Laboratory) (2024)
Open Access | Times Cited: 4
Evaluating ChatGPT’s diagnostic potential for pathology images
Liya Ding, Lei Fan, Miao Shen, et al.
Frontiers in Medicine (2025) Vol. 11
Open Access
The Diagnostic Classification of the Pathological Image Using Computer Vision
Yasunari Matsuzaka, Ryu Yashiro
Algorithms (2025) Vol. 18, Iss. 2, pp. 96-96
Open Access
An effective colorectal polyp classification for histopathological images based on supervised contrastive learning
Sena Busra Yengec-Tasdemir, Zafer Aydın, Ebru Akay, et al.
Computers in Biology and Medicine (2024) Vol. 172, pp. 108267-108267
Open Access | Times Cited: 3
FPGA implementation of deep learning architecture for kidney cancer detection from histopathological images
Shyam Lal, Amit Kumar Chanchal, Jyoti Kini, et al.
Multimedia Tools and Applications (2024) Vol. 83, Iss. 21, pp. 60583-60601
Closed Access | Times Cited: 2
AI-Based Anomaly Detection for Clinical-Grade Histopathological Diagnostics
Jonas Dippel, Niklas Prenißl, Julius Hense, et al.
NEJM AI (2024) Vol. 1, Iss. 11
Open Access | Times Cited: 2
Breaking Barriers: AI’s Influence on Pathology and Oncology in Resource-Scarce Medical Systems
Alon Vigdorovits, Maria Magdalena Köteles, G. Olteanu, et al.
Cancers (2023) Vol. 15, Iss. 23, pp. 5692-5692
Open Access | Times Cited: 5
Artificial intelligence in cancer pathology: Challenge to meet increasing demands of precision medicine
Boan Lai, Jianjiang Fu, Qingxin Zhang, et al.
International Journal of Oncology (2023) Vol. 63, Iss. 3
Closed Access | Times Cited: 4
Hyperplastic and Tubular Polyp Classification Using Machine Learning and Feature Selection
Refika Sultan Doğan, Ebru Akay, Serkan Doğan, et al.
Intelligence-Based Medicine (2024) Vol. 10, pp. 100177-100177
Open Access | Times Cited: 1
Classification and grade prediction of kidney cancer histological images using deep learning
Amit Kumar Chanchal, N Sravya, Shyam Lal, et al.
Multimedia Tools and Applications (2024) Vol. 83, Iss. 32, pp. 78247-78267
Closed Access
ANALYSIS AND CLASSIFICATION OF PATHOLOGY DIGITAL IMAGES USING DEEP LEARNING
G. Ravi, Pranav Nyavanandi, Vemulapally Jyotsna, et al.
International Research Journal of Modernization in Engineering Technology and Science (2024)
Open Access
Artificial intelligence in colonoscopy: from detection to diagnosis
Eun Sun Kim, Kwang‐Sig Lee
The Korean Journal of Internal Medicine (2024) Vol. 39, Iss. 4, pp. 555-562
Open Access
Estimating infant age from skull X-ray images using deep learning
H Lee, Jaewoong Kang, So Eui Kim, et al.
Scientific Reports (2024) Vol. 14, Iss. 1
Open Access
A deep learning approach to case prioritisation of colorectal biopsies
C. White, Runjan Chetty, John E. Weldon, et al.
Histopathology (2024)
Closed Access
Emerging Role of Artificial Intelligence in Colorectal Cancer: Screening and Diagnosis
Athanasia Mitsala, Christos Tsalikidis, Michael I. Koukourakis, et al.
Interdisciplinary cancer research (2024)
Closed Access
Explainability of a Deep Learning-Based Classification Model for ANCA-Associated Glomerulonephritis
Maria A C Wester Trejo, Maryam Sadeghi, Shivam Singh, et al.
Kidney International Reports (2024)
Open Access
Generative Artificial Intelligence in the Early Diagnosis of Gastrointestinal Disease
Kwang‐Sig Lee, Eun Sun Kim
Applied Sciences (2024) Vol. 14, Iss. 23, pp. 11219-11219
Open Access
Deep Learning Model to Diagnose Cardiac Amyloidosis from Hematoxylin/Eosin-Stained Myocardial Tissue
Takeshi Tohyama, Takeshi Iwasaki, Masataka Ikeda, et al.
European Heart Journal - Imaging Methods and Practice (2024) Vol. 3, Iss. 1
Closed Access
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