Machine Learning-Based Radiomics Nomogram for Detecting Extramural Venous Invasion in Rectal Cancer

Machine Learning-Based Radiomics Nomogram for Detecting Extramural Venous Invasion in Rectal Cancer

ObjectiveTo establish and validate a radiomics nomogram based on the features of the primary tumor for predicting preoperative pathological extramural venous invasion (EMVI) in rectal cancer using machine learning.MethodsThe clinical and imaging data of 281 patients with primary rectal cancer from A...

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Bibliographic Details
Main Authors: Siye Liu, Xiaoping Yu, Songhua Yang, Pingsheng Hu, Yingbin Hu, Xiaoyan Chen, Yilin Li, Zhe Zhang, Cheng Li, Qiang Lu
Format: Article
Language:English
Published: Frontiers Media S.A. 2021-03-01
Series:Frontiers in Oncology
Subjects:
rectal cancer
extramural venous invasion
radiomics
magnetic resonance imaging
computed tomography
prediction
Online Access:https://www.frontiersin.org/articles/10.3389/fonc.2021.610338/full

Internet

https://www.frontiersin.org/articles/10.3389/fonc.2021.610338/full

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