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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:

Deep neural network models for computational histopathology: A survey
Chetan L. Srinidhi, Ozan Ciga, Anne L. Martel
Medical Image Analysis (2020) Vol. 67, pp. 101813-101813
Open Access | Times Cited: 559

Showing 1-25 of 559 citing articles:

Review of deep learning: concepts, CNN architectures, challenges, applications, future directions
Laith Alzubaidi, Jinglan Zhang, Amjad J. Humaidi, et al.
Journal Of Big Data (2021) Vol. 8, Iss. 1
Open Access | Times Cited: 4715
Deep learning-enabled medical computer vision
Andre Esteva, Katherine Chou, Serena Yeung, et al.
npj Digital Medicine (2021) Vol. 4, Iss. 1
Open Access | Times Cited: 850
Deep learning in histopathology: the path to the clinic
Jeroen van der Laak, Geert Litjens, Francesco Ciompi
Nature Medicine (2021) Vol. 27, Iss. 5, pp. 775-784
Open Access | Times Cited: 599
Pan-cancer image-based detection of clinically actionable genetic alterations
Jakob Nikolas Kather, Lara R. Heij, Heike I. Grabsch, et al.
Nature Cancer (2020) Vol. 1, Iss. 8, pp. 789-799
Open Access | Times Cited: 481
Digital pathology and artificial intelligence in translational medicine and clinical practice
Vipul Baxi, Robin Edwards, Michael Montalto, et al.
Modern Pathology (2021) Vol. 35, Iss. 1, pp. 23-32
Open Access | Times Cited: 364
Harnessing multimodal data integration to advance precision oncology
Kevin M. Boehm, Pegah Khosravi, R. Vanguri, et al.
Nature reviews. Cancer (2021) Vol. 22, Iss. 2, pp. 114-126
Open Access | Times Cited: 321
Transformer-based unsupervised contrastive learning for histopathological image classification
Xiyue Wang, Sen Yang, Jun Zhang, et al.
Medical Image Analysis (2022) Vol. 81, pp. 102559-102559
Closed Access | Times Cited: 273
Artificial intelligence in histopathology: enhancing cancer research and clinical oncology
Artem Shmatko, Narmin Ghaffari Laleh, Moritz Gerstung, et al.
Nature Cancer (2022) Vol. 3, Iss. 9, pp. 1026-1038
Closed Access | Times Cited: 245
Human-interpretable image features derived from densely mapped cancer pathology slides predict diverse molecular phenotypes
James A. Diao, Jason K. Wang, Wan Fung Chui, et al.
Nature Communications (2021) Vol. 12, Iss. 1
Open Access | Times Cited: 182
GasHis-Transformer: A multi-scale visual transformer approach for gastric histopathological image detection
Haoyuan Chen, Chen Li, Ge Wang, et al.
Pattern Recognition (2022) Vol. 130, pp. 108827-108827
Open Access | Times Cited: 170
Deep learning for colon cancer histopathological images analysis
Amina Ben Hamida, Maxime Devanne, Jonathan Weber, et al.
Computers in Biology and Medicine (2021) Vol. 136, pp. 104730-104730
Open Access | Times Cited: 142
Robust whole slide image analysis for cervical cancer screening using deep learning
Shenghua Cheng, Sibo Liu, Jingya Yu, et al.
Nature Communications (2021) Vol. 12, Iss. 1
Open Access | Times Cited: 114
Hierarchical graph representations in digital pathology
Pushpak Pati, Guillaume Jaume, Antonio Foncubierta–Rodríguez, et al.
Medical Image Analysis (2021) Vol. 75, pp. 102264-102264
Open Access | Times Cited: 109
Deep learning: systematic review, models, challenges, and research directions
Tala Talaei Khoei, Hadjar Ould Slimane, Naima Kaabouch
Neural Computing and Applications (2023) Vol. 35, Iss. 31, pp. 23103-23124
Open Access | Times Cited: 108
Deep learning-based six-type classifier for lung cancer and mimics from histopathological whole slide images: a retrospective study
Huan Yang, Lili Chen, Zhiqiang Cheng, et al.
BMC Medicine (2021) Vol. 19, Iss. 1
Open Access | Times Cited: 107
Artificial intelligence assists precision medicine in cancer treatment
Jinzhuang Liao, M Kellis, Yu Gan, et al.
Frontiers in Oncology (2023) Vol. 12
Open Access | Times Cited: 98
Deconv-transformer (DecT): A histopathological image classification model for breast cancer based on color deconvolution and transformer architecture
He Zhu, Ming‐Wei Lin, Zeshui Xu, et al.
Information Sciences (2022) Vol. 608, pp. 1093-1112
Closed Access | Times Cited: 96
A promising deep learning-assistive algorithm for histopathological screening of colorectal cancer
Cowan Ho, Zitong Zhao, Xiu Fen Chen, et al.
Scientific Reports (2022) Vol. 12, Iss. 1
Open Access | Times Cited: 85
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: 82
Stacked LSTM Sequence-to-Sequence Autoencoder with Feature Selection for Daily Solar Radiation Prediction: A Review and New Modeling Results
Sujan Ghimire, Ravinesh C. Deo, Hua Wang, et al.
Energies (2022) Vol. 15, Iss. 3, pp. 1061-1061
Open Access | Times Cited: 76
A Morphology Focused Diffusion Probabilistic Model for Synthesis of Histopathology Images
Puria Azadi Moghadam, Sanne Van Dalen, Karina C. Martin, et al.
2022 IEEE/CVF Winter Conference on Applications of Computer Vision (WACV) (2023), pp. 1999-2008
Open Access | Times Cited: 58
A foundation model for clinical-grade computational pathology and rare cancers detection
Eugene Vorontsov, Alican Bozkurt, Adam Casson, et al.
Nature Medicine (2024) Vol. 30, Iss. 10, pp. 2924-2935
Open Access | Times Cited: 50
Artificial Intelligence in Breast Cancer Diagnosis and Personalized Medicine
Jong Seok Ahn, Sangwon Shin, Su‐A Yang, et al.
Journal of Breast Cancer (2023) Vol. 26, Iss. 5, pp. 405-405
Open Access | Times Cited: 49
Vision Transformers for Computational Histopathology
Hongming Xu, Qi Xu, Fengyu Cong, et al.
IEEE Reviews in Biomedical Engineering (2023) Vol. 17, pp. 63-79
Closed Access | Times Cited: 41
Computational Pathology: A Survey Review and The Way Forward
Mahdi S. Hosseini, Babak Ehteshami Bejnordi, Vincent Quoc‐Huy Trinh, et al.
Journal of Pathology Informatics (2024), pp. 100357-100357
Open Access | Times Cited: 32
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