| For: | Pellegrino R, Gravina AG. Machine learning as a tool predicting short-term postoperative complications in Crohn’s disease patients undergoing intestinal resection: What frontiers? World J Gastrointest Surg 2024; 16(9): 2755-2759 [PMID: 39351543 DOI: 10.4240/wjgs.v16.i9.2755] |
|---|---|
| URL: | https://www.wjgnet.com/1948-5190/full/v16/i9/2755.htm |
| Number | Citing Articles |
| 1 |
Lu‐Yen Anny Chen, Shu‐Yi Wang, Shu‐Chuan Amy Lin. Predicting Postoperative Outcomes in Lower Gastrointestinal Surgery: A Machine Learning Approach Using Electronic Health Records. AORN Journal 2026; 123(1): 68 doi: 10.1002/aorn.70000
|
| 2 |
Noha Alnazzawi. BERTDiseComp: A Clinical Language Model for Detecting Disease Complications in EHRs. 2025 International Conference on Electrical, Communication and Computer Engineering (ICECCE) 2025; : 1 doi: 10.1109/ICECCE67514.2025.11257959
|
| 3 |
Ye-Hui Fan, Ming-Wei Wang, Yu-Ning Gao, Wen-Mao Li, Yan Jiao. Genetic and environmental factors influencing Crohn’s disease. World Journal of Gastrointestinal Surgery 2025; 17(3): 98526 doi: 10.4240/wjgs.v17.i3.98526
|
