Assessing the value of deep neural networks for postoperative complication prediction in pancreaticoduodenectomy patients.
<h4>Introduction</h4>Pancreaticoduodenectomy (PD) for patients with pancreatic ductal adenocarcinoma (PDAC) is associated with a high risk of postoperative complications (PoCs) and risk prediction of these is therefore critical for optimal treatment planning. We hypothesize that novel de...
Saved in:
Main Authors: | Mikkel Bonde, Alexander Bonde, Haytham Kaafarani, Andreas Millarch, Martin Sillesen |
---|---|
Format: | Article |
Language: | English |
Published: |
Public Library of Science (PLoS)
2024-01-01
|
Series: | PLoS ONE |
Online Access: | https://doi.org/10.1371/journal.pone.0316402 |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
Assessing the value of deep neural networks for postoperative complication prediction in pancreaticoduodenectomy patients
by: Mikkel Bonde, et al.
Published: (2024-01-01) -
Radical Pancreaticoduodenectomy for Benign Disease
by: D. O. Kavanagh, et al.
Published: (2008-01-01) -
Predictive Factors of Early Recurrence in Patients with Distal Cholangiocarcinoma after Pancreaticoduodenectomy
by: Yasuhiro Ito, et al.
Published: (2018-01-01) -
Potential of hospital corneal retrieval program in tertiary care center
by: Ujwala Weladi, et al.
Published: (2025-01-01) -
Amalgam Tattoo Mimicking Mucosal Melanoma: A Diagnostic Dilemma Revisited
by: K. Lundin, et al.
Published: (2013-01-01)