Machine learning model based on enhanced CT radiomics for the preoperative prediction of lymphovascular invasion in esophageal squamous cell carcinoma

Machine learning model based on enhanced CT radiomics for the preoperative prediction of lymphovascular invasion in esophageal squamous cell carcinoma

ObjectiveTo evaluate the value of a machine learning model using enhanced CT radiomics features in the prediction of lymphovascular invasion (LVI) of esophageal squamous cell carcinoma (ESCC) before treatment.MethodsWe reviewed and analyzed the enhanced CT images of 258 ESCC patients from June 2017...

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Bibliographic Details
Main Authors: Yating Wang, Genji Bai, Min Huang, Wei Chen
Format: Article
Language:English
Published: Frontiers Media S.A. 2024-02-01
Series:Frontiers in Oncology
Subjects:
radiomics
machine learning
ESCC
lymphovascular invasion
computed tomography
Online Access:https://www.frontiersin.org/articles/10.3389/fonc.2024.1308317/full

Internet

https://www.frontiersin.org/articles/10.3389/fonc.2024.1308317/full

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