| For: | Huang YH, Lin Q, Jin XY, Chou CY, Wei JJ, Xing J, Guo HM, Liu ZF, Lu Y. Classification of pediatric video capsule endoscopy images for small bowel abnormalities using deep learning models. World J Gastroenterol 2025; 31(21): 107601 [PMID: 40538507 DOI: 10.3748/wjg.v31.i21.107601] |
|---|---|
| URL: | https://www.wjgnet.com/1007-9327/full/v31/i21/107601.htm |
| Number | Citing Articles |
| 1 |
T. Swetha Kumari, R. Vasuki, R. Kishore Kanna, S. Raju. A Comprehensive Review on Computer-Based Endoscopic Image Processing Using Machine Learning Application. 2025 International Conference on Electrical and Electronics Engineering (ICE3) 2025; doi: 10.1109/ICE367573.2025.11448910
|
| 2 |
Jeremy W. Stewart, Bradley A. Barth, Isabel Rojas. The utility of artificial intelligence in visualization of pediatric gastrointestinal mucosa. Frontiers in Pediatrics 2026; 13 doi: 10.3389/fped.2025.1739000
|
| 3 |
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
|
| 4 |
Tejashwini K, Karthik K, Jayakumar Jeganathan. A knowledge distillation framework integrating Grad-CAM in ResNet for imbalanced gastrointestinal abnormality classification in capsule endoscopy. Discover Artificial Intelligence 2026; 6(1) doi: 10.1007/s44163-026-01081-x
|