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A Machine Learning Approach to Predict Postoperative Pancreatic Fistula After Pancreaticoduodenectomy Using Only Preoperatively Known Data复制

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DOI: 10.1245/s10434-023-14041-x复制

文献链接: https://link.springer.com/10.1245/s10434-023-14041-x复制

其他信息:

出版社: Springer Science and Business Media LLC
作者: Amir Ashraf Ganjouei; Fernanda Romero-Hernandez; Jaeyun Jane Wang; Megan Casey; Willow Frye; Daniel Hoffman; Kenzo Hirose; Eric Nakakura; Carlos Corvera; Ajay V. Maker; Kimberly S. Kirkwood; Adnan Alseidi; Mohamed A. Adam
全文下载地址: https://link.springer.com/content/pdf/10.1245/s10434-023-14041-x.pdf

上一篇：Development of a Nomogram to Predict Clinically Relevant Postoperative Pancreatic Fistula After Pancreaticoduodenectomy on the Basis of Visceral Fat Area and Magnetic Resonance Imaging

下一篇：Differential Gains in Surgical Outcomes for High-Risk vs Low-Risk Pancreaticoduodenectomy with Successive Refinements of Risk-Stratified Care Pathways

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