Deep learning and radiomics fusion for predicting the invasiveness of lung adenocarcinoma within ground glass nodules

Deep learning and radiomics fusion for predicting the invasiveness of lung adenocarcinoma within ground glass nodules

Abstract Microinvasive adenocarcinoma (MIA) and invasive adenocarcinoma (IAC) require distinct treatment strategies and are associated with different prognoses, underscoring the importance of accurate differentiation. This study aims to develop a predictive model that combines radiomics and deep lea...

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Bibliographic Details
Main Authors: Qian Sun, Lei Yu, Zhongquan Song, Can Wang, Wei Li, Wang Chen, Juan Xu, Shuhua Han
Format: Article
Language:English
Published: Nature Portfolio 2025-08-01
Series:Scientific Reports
Subjects:
Ground-glass nodule
Deep learning
Radiomics
Invasive adenocarcinoma
Fusion model
Online Access:https://doi.org/10.1038/s41598-025-13447-9
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https://doi.org/10.1038/s41598-025-13447-9

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