CT radiomics combined with neural networks predict the malignant degree of pulmonary grinding glass nodules

CT radiomics combined with neural networks predict the malignant degree of pulmonary grinding glass nodules

BackgroundThis study investigates the use of CT radiomics combined with convolutional neural networks (CNN) to predict the malignancy of lung ground glass nodules (GGN), which are challenging to diagnose due to their ambiguous boundaries. The goal is to improve diagnostic accuracy and support person...

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Bibliographic Details
Main Authors: Pengfei Chen, Huiyuan Gong, Lei Zhang, Yang Geng
Format: Article
Language:English
Published: Frontiers Media S.A. 2025-07-01
Series:Frontiers in Medicine
Subjects:
convolutional neural network
lung ground glass nodules
CT radiomics
infiltration
predictive modelling
Online Access:https://www.frontiersin.org/articles/10.3389/fmed.2025.1603472/full
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