Development of a multi-feature-combined model: proof-of-concept with application to local failure prediction of post-SBRT or surgery early-stage NSCLC patients

Development of a multi-feature-combined model: proof-of-concept with application to local failure prediction of post-SBRT or surgery early-stage NSCLC patients

ObjectiveTo develop a Multi-Feature-Combined (MFC) model for proof-of-concept in predicting local failure (LR) in NSCLC patients after surgery or SBRT using pre-treatment CT images. This MFC model combines handcrafted radiomic features, deep radiomic features, and patient demographic information in...

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Bibliographic Details
Main Authors: Zhenyu Yang, Chunhao Wang, Yuqi Wang, Kyle J. Lafata, Haozhao Zhang, Bradley G. Ackerson, Christopher Kelsey, Betty Tong, Fang-Fang Yin
Format: Article
Language:English
Published: Frontiers Media S.A. 2023-09-01
Series:Frontiers in Oncology
Subjects:
early-stage lung NSCLC
local failure
surgery
SBRT
machine learning (ML)
deep learning
Online Access:https://www.frontiersin.org/articles/10.3389/fonc.2023.1185771/full

Internet

https://www.frontiersin.org/articles/10.3389/fonc.2023.1185771/full

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