| For: | Akbulut S, Kucukakcali Z, Colak C. Artificial intelligence in acute appendicitis: A comprehensive review of machine learning and deep learning applications. World J Gastroenterol 2025; 31(43): 112000 [PMID: 41358178 DOI: 10.3748/wjg.v31.i43.112000] |
|---|---|
| URL: | https://www.wjgnet.com/2307-8960/full/v31/i43/112000.htm |
| Number | Citing Articles |
| 1 |
Ceren Altintas Mese, Ismail Mese, Tugba Akinci D’Antonoli. Zero-shot performance of a general-purpose vision-language model for pediatric appendicitis diagnosis. Pediatric Radiology 2026; doi: 10.1007/s00247-026-06687-y
|
| 2 |
Margarita L. Martinez-Fierro, Jose G. Gonzalez-Rodarte, Sodel Vazquez-Reyes, Manuel Gonzalez-Plascencia, Idalia Garza-Veloz, Perla Velasco-Elizondo, Sidere M. Zorrilla-Alfaro, Jaime Y. Burciaga-Paez, Gonzalo Ibarra-Bañuelos, Luis A. Flores-Chaires, Alejandro Mauricio-Gonzalez. Usefulness of Laboratory-Based Machine Learning for Detection and Severity Classification of Acute Appendicitis in a Resource-Limited Healthcare Setting. Diagnostics 2026; 16(7) doi: 10.3390/diagnostics16071090
|
| 3 |
Erkan Karacan, H. Mehmet Kayili. Machine learning-based diagnostic modeling for differentiating lymphoid hyperplasia from acute appendicitis using laboratory biomarkers. The American Journal of Surgery 2026; 256 doi: 10.1016/j.amjsurg.2026.116925
|
| 4 |
Xuhong Zhang, Xiaoyu Wang, Hong Zhu, Huiwen Yu, Lin Fu, Wanyi Shu, Xihang Ye, Zhixin Lim, Saboor Saeed, Ha Linh Nguyen, Julius Pistoor, Dazhong Rong, Jianbo Lai, Zheng Wang, Yang He, Yueming Wang, Ye Shen, Yudong Zhou, Shaohua Hu, Jianping Tong. Eye–brain axis: Ocular and visual pathophysiology as driver and therapeutic target across the mood disorder trajectory. Progress in Retinal and Eye Research 2026; 112 doi: 10.1016/j.preteyeres.2026.101467
|