Development and validation of a CT-based deep learning radiomics nomogram to predict muscle invasion in bladder cancer

Development and validation of a CT-based deep learning radiomics nomogram to predict muscle invasion in bladder cancer

Objective: This study aimed to develop a nomogram combining CT-based handcrafted radiomics and deep learning (DL) features to preoperatively predict muscle invasion in bladder cancer (BCa) with multi-center validation. Methods: In this retrospective study, 323 patients underwent radical cystectomy w...

Full description

Bibliographic Details
Main Authors: Zongjie Wei, Huayun Liu, Yingjie Xv, Fangtong Liao, Quanhao He, Yongpeng Xie, Fajin Lv, Qing Jiang, Mingzhao Xiao
Format: Article
Language:English
Published: Elsevier 2024-01-01
Series:Heliyon
Subjects:
Radiomics
Deep learning
Bladder cancer
Computed tomography
Nomogram
Online Access:http://www.sciencedirect.com/science/article/pii/S2405844024009095

Internet

http://www.sciencedirect.com/science/article/pii/S2405844024009095

Similar Items