Multiscale deep learning radiomics for predicting recurrence-free survival in pancreatic cancer: A multicenter study

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作者信息关键词期刊信息基础信息归属信息摘要

成果类型：

期刊论文

作者：

Gu, Qianbiao;Sun, Huiling;Liu, Peng;Hu, Xiaoli;Yang, Jiankang;...

通讯作者：

Xing, Y

作者机构：

[Xing, Yan; Gu, Qianbiao] Xinjiang Med Univ, Affiliated Hosp 1, Imaging Ctr, Urumqi 830011, Peoples R China.

[Sun, Huiling] Tradit Chinese Med Hosp Changji Hui Autonomous Pre, Dept CT & MR, Changji 831100, Changji Hui Aut, Peoples R China.

[Liu, Peng] Hunan Normal Univ, Hunan Prov Peoples Hosp, Affiliated Hosp 1, Dept Radiol, Changsha 410000, Peoples R China.

[Hu, Xiaoli] Hunan Univ Chinese Med, Affiliated Hosp 1, Dept Radiol, Changsha 410000, Peoples R China.

[Yang, Jiankang] YueYang Cent Hosp, Dept Radiol, Yueyang 414000, Peoples R China.

通讯机构：

[Xing, Y ] X

Xinjiang Med Univ, Affiliated Hosp 1, Imaging Ctr, Urumqi 830011, Peoples R China.

语种：

英文

关键词：

Deep learning radiomics;Imaging biomarker;Pancreatic ductal adenocarcinoma (PDAC);Prognosis

期刊：

Radiotherapy and Oncology

ISSN：

0167-8140

年：

2025

卷：

205

页码：

110770

DOI：

10.1016/j.radonc.2025.110770

基金类别：

No funding was received for this study.

机构署名：

本校为其他机构

院系归属：

第一中医临床学院

摘要：

Purpose This multicenter study aimed to develop and validate a multiscale deep learning radiomics nomogram for predicting recurrence-free survival (RFS) in patients with pancreatic ductal adenocarcinoma (PDAC). This multicenter study aimed to develop and validate a multiscale deep learning radiomics nomogram for predicting recurrence-free survival (RFS) in patients with pancreatic ductal adenocarcinoma (PDAC). Materials and methods A total of 469 PDAC patients from four hospitals were divided into training and test sets. Handcrafted radiomics a...

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Multiscale deep learning radiomics for predicting recurrence-free survival in pancreatic cancer: A multicenter study

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