For: | Chu Y, Huang F, Gao M, Zou DW, Zhong J, Wu W, Wang Q, Shen XN, Gong TT, Li YY, Wang LF. Convolutional neural network-based segmentation network applied to image recognition of angiodysplasias lesion under capsule endoscopy. World J Gastroenterol 2023; 29(5): 879-889 [PMID: 36816625 DOI: 10.3748/wjg.v29.i5.879] |
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URL: | https://www.wjgnet.com/1007-9327/full/v29/i5/879.htm |
Number | Citing Articles |
1 |
Ahmmad Musha, Rehnuma Hasnat, Abdullah Al Mamun, Em Poh Ping, Tonmoy Ghosh. Computer-Aided Bleeding Detection Algorithms for Capsule Endoscopy: A Systematic Review. Sensors 2023; 23(16): 7170 doi: 10.3390/s23167170
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Francisco Mendes, Miguel Mascarenhas, Tiago Ribeiro, João Afonso, Pedro Cardoso, Miguel Martins, Hélder Cardoso, Patrícia Andrade, João P. S. Ferreira, Miguel Mascarenhas Saraiva, Guilherme Macedo. Artificial Intelligence and Panendoscopy—Automatic Detection of Clinically Relevant Lesions in Multibrand Device-Assisted Enteroscopy. Cancers 2024; 16(1): 208 doi: 10.3390/cancers16010208
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Joana Mota, Maria João Almeida, Francisco Mendes, Miguel Martins, Tiago Ribeiro, João Afonso, Pedro Cardoso, Helder Cardoso, Patrícia Andrade, João Ferreira, Miguel Mascarenhas, Guilherme Macedo. From Data to Insights: How Is AI Revolutionizing Small-Bowel Endoscopy?. Diagnostics 2024; 14(3): 291 doi: 10.3390/diagnostics14030291
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Rui-Ya Zhang, Peng-Peng Qiang, Ling-Jun Cai, Tao Li, Yan Qin, Yu Zhang, Yi-Qing Zhao, Jun-Ping Wang. Automatic detection of small bowel lesions with different bleeding risks based on deep learning models. World Journal of Gastroenterology 2024; 30(2): 170-183 doi: 10.3748/wjg.v30.i2.170
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