Meeting Banner
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.

This abstract and the presentation materials are available to members only; a login is required.

Join Here