Ensemble Machine Learning Classifiers Combining CT Radiomics and Clinical-Radiological Features for Preoperative Prediction of Pathological Invasiveness in Lung Adenocarcinoma Presenting as Part-Solid Nodules: A Multicenter Retrospective Study

Ensemble Machine Learning Classifiers Combining CT Radiomics and Clinical-Radiological Features for Preoperative Prediction of Pathological Invasiveness in Lung Adenocarcinoma Presenting as Part-Solid Nodules: A Multicenter Retrospective Study

Background Lung adenocarcinomas manifesting as part-solid nodules (PSNs) represent a distinct clinical subtype where accurate preoperative determination of pathological invasiveness critically influences both prognosis and surgical decision-making. This multicenter study aims to develop an ensemble...

Full description

Saved in:
Bibliographic Details
Main Authors: Yunhua Li BS, Jianbang Ding MS, Kun Wu MS, Wanyin Qi BS, Shanyue Lin BS, Gangwen Chen BS, Zhichao Zuo PhD
Format: Article
Language:English
Published: SAGE Publishing 2025-06-01
Series:Technology in Cancer Research & Treatment
Online Access:https://doi.org/10.1177/15330338251351365
Tags: Add Tag
No Tags, Be the first to tag this record!

Internet

https://doi.org/10.1177/15330338251351365

Similar Items