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Cited by in CrossRef
For: Zhang RY, Qiang PP, Cai LJ, Li T, Qin Y, Zhang Y, Zhao YQ, Wang JP. Automatic detection of small bowel lesions with different bleeding risks based on deep learning models. World J Gastroenterol 2024; 30(2): 170-183 [PMID: 38312122 DOI: 10.3748/wjg.v30.i2.170]
URL: https://www.wjgnet.com/1007-9327/full/v30/i2/170.htm
Number Citing Articles
1
Jinseo Jeong, Sohyun Kim, Lian Pan, Daye Hwang, Dongseop Kim, Jeongwon Choi, Yeongkyo Kwon, Pyeongro Yi, Jisoo Jeong, Seok-Ju Yoo. Reducing the workload of medical diagnosis through artificial intelligence: A narrative reviewMedicine 2025; 104(6): e41470 doi: 10.1097/MD.0000000000041470
2
Naim Rochmawati, Chastine Fatichah, Bilqis Amaliah, Agus Budi Raharjo, Frédéric Dumont, Emilie Thibaudeau, Cédric Dumas. Deep Learning-Based Lesion Detection in Endoscopy: A Systematic Literature ReviewIEEE Access 2025; 13: 43532 doi: 10.1109/ACCESS.2025.3548167
3
Shiren Ye, Shuo Zhang, Qi Meng, Hui Wang, Jiaqun Zhu. Disease Detection Module for SBCE Images Using Modified YOLOv82024 IEEE International Conference on Systems, Man, and Cybernetics (SMC) 2024; : 5175 doi: 10.1109/SMC54092.2024.10831442
4
Silvia Cocca, Giuseppina Pontillo, Giuseppe Grande, Rita Conigliaro. Artificial intelligence in detection of small bowel lesions and their bleeding risk: A new step forwardWorld Journal of Gastroenterology 2024; 30(18): 2482-2484 doi: 10.3748/wjg.v30.i18.2482
5
Wenli He, Lina He. Study of Automatic Diagnostic Algorithms for Small Bowel Lesions in Capsule Endoscopic ImagesProceedings of the 2024 4th International Conference on Artificial Intelligence, Big Data and Algorithms 2024; : 890 doi: 10.1145/3690407.3690555