MRI-based random survival Forest model improves prediction of progression-free survival to induction chemotherapy plus concurrent Chemoradiotherapy in Locoregionally Advanced nasopharyngeal carcinoma

MRI-based random survival Forest model improves prediction of progression-free survival to induction chemotherapy plus concurrent Chemoradiotherapy in Locoregionally Advanced nasopharyngeal carcinoma

Abstract Background The present study aimed to explore the application value of random survival forest (RSF) model and Cox model in predicting the progression-free survival (PFS) among patients with locoregionally advanced nasopharyngeal carcinoma (LANPC) after induction chemotherapy plus concurrent...

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Bibliographic Details
Main Authors: Wei Pei, Chen Wang, Hai Liao, Xiaobo Chen, Yunyun Wei, Xia Huang, Xueli Liang, Huayan Bao, Danke Su, Guanqiao Jin
Format: Article
Language:English
Published: BMC 2022-07-01
Series:BMC Cancer
Subjects:
Nasopharyngeal carcinoma
Magnetic resonance imaging
Radiomics
Machine learning
Radom survival forest
Online Access:https://doi.org/10.1186/s12885-022-09832-6

Internet

https://doi.org/10.1186/s12885-022-09832-6

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