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Cited by in CrossRef
For: Ogura M, Kiyuna T, Yoshida H. Impact of blurs on machine-learning aided digital pathology image analysis. Artif Intell Cancer 2020; 1(1): 31-38 [DOI: 10.35713/aic.v1.i1.31]
URL: https://www.wjgnet.com/2644-3228/full/v1/i1/31.htm
Number Citing Articles
1
Enrico Giarnieri, Simone Scardapane. Towards Artificial Intelligence Applications in Next Generation CytopathologyBiomedicines 2023; 11(8): 2225 doi: 10.3390/biomedicines11082225
2
Romain Brixtel, Sebastien Bougleux, Olivier Lezoray, Yann Caillot, Benoit Lemoine, Mathieu Fontaine, Dalal Nebati, Arnaud Renouf. Whole Slide Image Quality in Digital Pathology: Review and PerspectivesIEEE Access 2022; 10: 131005 doi: 10.1109/ACCESS.2022.3227437
3
A.M.S.K. Abeysinghe, G. Anthonys. Nutrient Deficiency Detection System for Black Pepper Leaf using Machine Learning2024 8th SLAAI International Conference on Artificial Intelligence (SLAAI-ICAI) 2024; : 1 doi: 10.1109/SLAAI-ICAI63667.2024.10844967
4
Paul Barthe, Romain Brixtel, Yann Caillot, Benoît Lemoine, Arnaud Renouf, Vianney Thurotte, Ouarda Beniken, Sébastien Bougleux, Olivier Lézoray. Assessing the quality of whole slide images in cytology from nuclei featuresJournal of Pathology Informatics 2025; 17: 100420 doi: 10.1016/j.jpi.2025.100420
5
Yuxuan Sun, Chenglu Zhu, Yunlong Zhang, Honglin Li, Pingyi Chen, Lin Yang. Assessing the Robustness of Deep Learning-Assisted Pathological Image Analysis Under Practical Variables of Imaging SystemICASSP 2023 - 2023 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP) 2023; : 1 doi: 10.1109/ICASSP49357.2023.10095887
6
Chen Sagiv, Ofir Hadar, Abderrahman Najjar, Jens Pahnke. Artificial intelligence in surgical pathology – Where do we stand, where do we go?European Journal of Surgical Oncology 2024; : 109541 doi: 10.1016/j.ejso.2024.109541