| For: | Wang YY, Liu B, Wang JH. Application of deep learning-based convolutional neural networks in gastrointestinal disease endoscopic examination. World J Gastroenterol 2025; 31(36): 111137 [PMID: 41025070 DOI: 10.3748/wjg.v31.i36.111137] |
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| URL: | https://www.wjgnet.com/1007-9327/full/v31/i36/111137.htm |
| Number | Citing Articles |
| 1 |
Ning Wang, Jiajing Lin, Wujin Li, Yahui Lyu, Yiqing Jiang, Zhizhan Ni, Qi Huang, Hong Chen, Qiang Yan, Chenshen Huang. Deep multimodal state-space fusion of endoscopic-radiomic and clinical data for survival prediction in colorectal cancer. npj Digital Medicine 2025; 8(1) doi: 10.1038/s41746-025-02236-3
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| 2 |
Divyanshi Sood, Surbhi Dadwal, Samiksha Jain, Iqra Jabeen Mazhar, Bipasha Goyal, Chris Garapati, Sagar Patel, Zenab Muhammad Riaz, Noor Buzaboon, Ayushi Mendiratta, Avneet Kaur, Anmol Mohan, Gayathri Yerrapragada, Poonguzhali Elangovan, Mohammed Naveed Shariff, Thangeswaran Natarajan, Jayarajasekaran Janarthanan, Shreshta Agarwal, Sancia Mary Jerold Wilson, Atishya Ghosh, Shiva Sankari Karuppiah, Joshika Agarwal, Keerthy Gopalakrishnan, Swetha Rapolu, Venkata S. Akshintala, Shivaram P. Arunachalam. Prospective of Colorectal Cancer Screening, Diagnosis, and Treatment Management Using Bowel Sounds Leveraging Artificial Intelligence. Cancers 2026; 18(2): 340 doi: 10.3390/cancers18020340
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| 3 |
Hui Nian, Yi-Bin Wu, Yu Bai, Zhi-Long Zhang, Xiao-Huang Tu, Qi-Zhi Liu, De-Hua Zhou, Qian-Cheng Du. Multimodal artificial intelligence integrates imaging, endoscopic, and omics data for intelligent decision-making in individualized gastrointestinal tumor treatment. Artificial Intelligence in Gastroenterology 2026; 7(1): 115498 doi: 10.35712/aig.v7.i1.115498
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| 4 |
Yuanyuan Xiang. Medical Image Classification Using U-KAN Architecture for Gastrointestinal Pathology Detection. 2025 4th International Conference on Image Processing, Computer Vision and Machine Learning (ICICML) 2025; : 1442 doi: 10.1109/ICICML67980.2025.11333778
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| 5 |
Wanyu Qiu, Xiao Yang, Zirui Liu, Chen Qiu. Advancing Real-Time Polyp Detection in Colonoscopy Imaging: An Anchor-Free Deep Learning Framework with Adaptive Multi-Scale Perception. Sensors 2025; 25(24): 7524 doi: 10.3390/s25247524
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