For: | Cai YW, Dong FF, Shi YH, Lu LY, Chen C, Lin P, Xue YS, Chen JH, Chen SY, Luo XB. Deep learning driven colorectal lesion detection in gastrointestinal endoscopic and pathological imaging. World J Clin Cases 2021; 9(31): 9376-9385 [PMID: 34877273 DOI: 10.12998/wjcc.v9.i31.9376] |
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URL: | https://www.wjgnet.com/2307-8960/full/v9/i31/9376.htm |
Number | Citing Articles |
1 |
Masayuki Tsuneki. Deep learning models in medical image analysis. Journal of Oral Biosciences 2022; 64(3): 312 doi: 10.1016/j.job.2022.03.003
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2 |
Magdalena Leśniewska, Rafał Patryn, Agnieszka Kopystecka, Ilona Kozioł, Julia Budzyńska. Third Eye? The Assistance of Artificial Intelligence (AI) in the Endoscopy of Gastrointestinal Neoplasms. Journal of Clinical Medicine 2023; 12(21): 6721 doi: 10.3390/jcm12216721
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3 |
Yule Wang, Yimin Yin, Renye Zhang, Jinghua Zhang. Deep Learning-based Histopathological Image Classification of Colorectal Cancer: A Brief Survey of Recent Trends. Proceedings of the 2023 6th International Conference on Computational Intelligence and Intelligent Systems 2023; : 139 doi: 10.1145/3638209.3638230
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4 |
Xiaoyu Fan, Yiming Yan, Yafei Li, Yu Song, Bo Li. Anti-tumor mechanism of artesunate. Frontiers in Pharmacology 2024; 15 doi: 10.3389/fphar.2024.1483049
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5 |
F. van den Noort, F. ter Borg, A. Guitink, J. Faber, J. M. Wolterink. Deep learning for segmentation of colorectal carcinomas on endoscopic ultrasound. Techniques in Coloproctology 2025; 29(1) doi: 10.1007/s10151-024-03056-5
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6 |
Junbo Gao, Junru Liang, Junlong Li, Wei Sun, Guoqiang Qu. White-light endoscopic colorectal lesion detection based on improved YOLOv7. Biomedical Signal Processing and Control 2024; 90: 105897 doi: 10.1016/j.bspc.2023.105897
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7 |
Ryuji Hamamoto, Takafumi Koyama, Nobuji Kouno, Tomohiro Yasuda, Shuntaro Yui, Kazuki Sudo, Makoto Hirata, Kuniko Sunami, Takashi Kubo, Ken Takasawa, Satoshi Takahashi, Hidenori Machino, Kazuma Kobayashi, Ken Asada, Masaaki Komatsu, Syuzo Kaneko, Yasushi Yatabe, Noboru Yamamoto. Introducing AI to the molecular tumor board: one direction toward the establishment of precision medicine using large-scale cancer clinical and biological information. Experimental Hematology & Oncology 2022; 11(1) doi: 10.1186/s40164-022-00333-7
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