Deep learning radiomics fusion model to predict visceral pleural invasion of clinical stage IA lung adenocarcinoma: a multicenter study

Deep learning radiomics fusion model to predict visceral pleural invasion of clinical stage IA lung adenocarcinoma: a multicenter study

Abstract Aim To assess the predictive performance, risk stratification capabilities, and auxiliary diagnostic utility of radiomics, deep learning, and fusion models in identifying visceral pleural invasion (VPI) in lung adenocarcinoma. Materials and methods A total of 449 patients (female:male, 263:...

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Bibliographic Details
Main Authors: Jiabi Zhao, Tingting Wang, Bin Wang, Bhuva Maheshkumar Satishkumar, Lumin Ding, Xiwen Sun, Caizhong Chen
Format: Article
Language:English
Published: BMC 2025-05-01
Series:Journal of Cardiothoracic Surgery
Subjects:
Radiomics
Deep learning
Adenocarcinoma of lung
CT
Online Access:https://doi.org/10.1186/s13019-025-03488-6
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https://doi.org/10.1186/s13019-025-03488-6

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