| 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] |
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| URL: | https://www.wjgnet.com/1007-9327/full/v30/i2/170.htm |
| Number | Citing Articles |
| 1 |
Ali Sahafi, Anastasios Koulaouzidis, Amin Naemi. Artificial Intelligence in Gastrointestinal Wireless Capsule Endoscopy: A Systematic Literature Review and Meta-Analysis. Diagnostics 2026; 16(9) doi: 10.3390/diagnostics16091269
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| 2 |
Daniele Salvi, Chiara Zani, Cristiano Spada, Stefania Piccirelli, Lorenzo Zileri Dal Verme, Giulia Tripodi, Loredana Gualtieri, Paola Cesaro, Clarissa Ferrari. Neural Network Architectures in Video Capsule Endoscopy: A Systematic Review and Meta-Analysis on Accuracy and Reading Time Performances. Applied Sciences 2026; 16(2) doi: 10.3390/app16021134
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| 3 |
Hongzhen Zhang, Feng Zhao. Deep learning meets clinical practice: A You Only Look Once–based framework for accurate and real-time detection of carotid vulnerable plaques. Journal of International Medical Research 2026; 54(2) doi: 10.1177/03000605261420504
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| 4 |
Shiren Ye, Liangjing Li, Zetong Zhang, Haipeng Ma. YOLOv12-WCIRS: An Improved YOLOv12-Based Framework for Small Intestinal Lesion Detection in WCE. Computers 2026; 15(5) doi: 10.3390/computers15050283
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| 5 |
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 review. Medicine 2025; 104(6) doi: 10.1097/MD.0000000000041470
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| 6 |
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 Review. IEEE Access 2025; 13 doi: 10.1109/ACCESS.2025.3548167
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| 7 |
A. F. Kanev, О. S. Kobyakova, N. G. Kurakova, R. L. Karmina. The impact of AI solutions on reducing the administrative and operational burden on medical personnel in the healthcare system. Public Health 2026; 6(1) doi: 10.21045/2782-1676-2026-6-1-28-39
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| 8 |
Fan Huang, Jinghao Li, Yangsong Zhang, Xiaoan Li. GAD-YOLO: a gastrointestinal abnormality detection YOLO model with multi-scale channel attention and residual fusion. Medical & Biological Engineering & Computing 2026; 64(5) doi: 10.1007/s11517-026-03526-y
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| 9 |
Peipei Wang, Yu Liu, Yuanjun Wang. Automatic Localization and Classification of Crohn’s Disease Activity in Computed Tomography Enterography Images Using Deep Learning. Journal of Imaging Informatics in Medicine 2026; doi: 10.1007/s10278-025-01838-3
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| 10 |
Shiren Ye, Shuo Zhang, Qi Meng, Hui Wang, Jiaqun Zhu. Disease Detection Module for SBCE Images Using Modified YOLOv8. 2024 IEEE International Conference on Systems, Man, and Cybernetics (SMC) 2024; doi: 10.1109/SMC54092.2024.10831442
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| 11 |
Silvia Cocca, Giuseppina Pontillo, Giuseppe Grande, Rita Conigliaro. Artificial intelligence in detection of small bowel lesions and their bleeding risk: A new step forward. World Journal of Gastroenterology 2024; 30(18): 2482-2484 doi: 10.3748/wjg.v30.i18.2482
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| 12 |
Wenli He, Lina He. Study of Automatic Diagnostic Algorithms for Small Bowel Lesions in Capsule Endoscopic Images. Proceedings of the 2024 4th International Conference on Artificial Intelligence, Big Data and Algorithms 2024; doi: 10.1145/3690407.3690555
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