Letter to Editor Regarding Article “A Machine Learning Approach to Predict Postoperative Pancreatic Fistula After Pancreaticoduodenectomy Using Only Preoperatively Known Data”
Author:
Publisher
Springer Science and Business Media LLC
Link
https://link.springer.com/content/pdf/10.1245/s10434-024-15237-5.pdf
Reference5 articles.
1. Ashraf Ganjouei A, et al. A Machine learning approach to predict postoperative pancreatic fistula after pancreaticoduodenectomy using only preoperatively known data. Ann Surg Oncol. 2023;30(12):7738–47.
2. Watanabe G, et al. Evaluation of pancreatic chymotrypsin activity for on-site prediction of clinically relevant postoperative pancreatic fistula. Pancreatology. 2023;24:169–77.
3. Rykina-Tameeva N, et al. Non-surgical interventions for the prevention of clinically relevant postoperative pancreatic fistula-a narrative review. Cancers (Basel). 2023;15(24):5865.
4. Wu Y, et al. C-reactive protein/albumin and C-reactive protein/fibrinogen ratios for the diagnosis of periprosthetic joint infection in revision total joint arthroplasty. Int Immunopharmacol. 2023;115:109682.
5. Yang Y, Hu J, Wang Z. Letter to editor regarding article “Multidimensional nomogram to predict postoperative pancreatic fistula after minimally invasive pancreaticoduodenectomy.” Ann Surg Oncol. 2023;31:1956.
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