Imaging-Based Deep Graph Neural Networks for Survival Analysis in Early Stage Lung Cancer Using CT: A Multicenter Study
BackgroundLung cancer is the leading cause of cancer-related mortality, and accurate prediction of patient survival can aid treatment planning and potentially improve outcomes. In this study, we proposed an automated system capable of lung segmentation and survival prediction using graph convolution...
Main Authors: | Jie Lian, Yonghao Long, Fan Huang, Kei Shing Ng, Faith M. Y. Lee, David C. L. Lam, Benjamin X. L. Fang, Qi Dou, Varut Vardhanabhuti |
---|---|
Format: | Article |
Language: | English |
Published: |
Frontiers Media S.A.
2022-07-01
|
Series: | Frontiers in Oncology |
Subjects: | |
Online Access: | https://www.frontiersin.org/articles/10.3389/fonc.2022.868186/full |
Similar Items
-
Predicting CT-Based Coronary Artery Disease Using Vascular Biomarkers Derived from Fundus Photographs with a Graph Convolutional Neural Network
by: Fan Huang, et al.
Published: (2022-06-01) -
Survival analysis in clinical trials: Basics and must know areas
by: Ritesh Singh, et al.
Published: (2011-01-01) -
Stepwise cox regression analysis in SPSS
by: Sampada Dessai, et al.
Published: (2018-01-01) -
Spherical Convolutional Neural Networks for Survival Rate Prediction in Cancer Patients
by: Fabian Sinzinger, et al.
Published: (2022-04-01) -
Analisis Regresi COX Proportional Hazard pada Pemodelan Waktu Tunggu Mendapatkan Pekerjaan
by: Hendra H. Dukalang
Published: (2019-01-01)