Artificial intelligence for assessment of vascular involvement and tumor resectability on CT in patients with pancreatic cancer

Abstract Objective This study aimed to develop and evaluate an automatic model using artificial intelligence (AI) for quantifying vascular involvement and classifying tumor resectability stage in patients with pancreatic ductal adenocarcinoma (PDAC), primarily to support radiologists in referral cen...

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Auteurs principaux:	Jacqueline I. Bereska, Boris V. Janssen, C. Yung Nio, Marnix P. M. Kop, Geert Kazemier, Olivier R. Busch, Femke Struik, Henk A. Marquering, Jaap Stoker, Marc G. Besselink, Inez M. Verpalen, for the Pancreatobiliary and Hepatic Artificial Intelligence Research (PHAIR) consortium
Format:	Artigo
Langue:	Inglês
Publié:	SpringerOpen 2024-02-01
Collection:	European Radiology Experimental
Sujets:	Artificial intelligence Carcinoma (pancreatic ductal) Pancreatic neoplasms Tomography (x-ray computed) Unsupervised machine learning
Accès en ligne:	https://doi.org/10.1186/s41747-023-00419-9
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