Prediction of lymph node metastasis in lung adenocarcinoma using a PET/CT radiomics-based ensemble learning model and its pathological basis

Prediction of lymph node metastasis in lung adenocarcinoma using a PET/CT radiomics-based ensemble learning model and its pathological basis

ObjectivesLymph node metastasis (LNM) is an important factor affecting the stage and prognosis of patients with lung adenocarcinoma. The purpose of this study is to explore the predictive value of the stacking ensemble learning model based on 18F-FDG PET/CT radiomic features and clinical risk factor...

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Bibliographic Details
Main Authors: Shulin Li, Fang Chen, Lei Wang, Zhiming Xiang
Format: Article
Language:English
Published: Frontiers Media S.A. 2025-08-01
Series:Frontiers in Oncology
Subjects:
lung adenocarcinoma
lymph node metastasis
positron emission tomography
radiomics
pathomics
stacking ensemble learning
Online Access:https://www.frontiersin.org/articles/10.3389/fonc.2025.1618494/full
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