Abstract #3138

A time-related random forest survival model based on MR imaging markers to predict the survival of patients with nasopharyngeal carcinoma

Chao Luo¹, Haixia Li², Kan Deng², and Haojiang Li¹

¹Sun Yat-sen University Cancer Center, Guangzhou, China, ²Philips Healthcare, Guangzhou, China

Synopsis

This study aimed to identify magnetic resonance (MR) imaging markers associated with the overall survival (OS) of patients with nasopharyngeal carcinoma (NPC) and establish a random survival forest (RSF) model, which is a time-related machine learning model for survival analysis, to predict their survival.

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