Identification of prognostic signatures in remnant gastric cancer through an interpretable risk model based on machine learning: a multicenter cohort study

Abstract Objective The purpose of this study was to develop an individual survival prediction model based on multiple machine learning (ML) algorithms to predict survival probability for remnant gastric cancer (RGC). Methods Clinicopathologic data of 286 patients with RGC undergoing operation (radic...

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Principais autores:	Zhouwei Zhan, Bijuan Chen, Hui Cheng, Shaohua Xu, Chunping Huang, Sijing Zhou, Haiting Chen, Xuanping Lin, Ruyu Lin, Wanting Huang, Xiaohuan Ma, Yu Fu, Zhipeng Chen, Hanchen Zheng, Songchang Shi, Zengqing Guo, Lihui Zhang
Format:	Artigo
Jezik:	Inglês
Izdano:	BMC 2024-04-01
Serija:	BMC Cancer
Teme:	Remnant gastric cancer Prognosis Prediction model Machine learning Interpretable Multicenter
Online dostop:	https://doi.org/10.1186/s12885-024-12303-9
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