Article

Early-Stage NSCLC Patients’ Prognostic Prediction with Multi-information Using Transformer and Graph Neural Network Model

2022-06-16

Abstract excerpt

<h4>Background</h4> We proposed a population graph with Transformer-generated and clinical features for the purpose of predicting overall survival and recurrence-free survival for patients with early-stage NSCLC and to compare this model with traditional models. <h4>Methods</h4> The study included 1705 patients with lung cancer (stage I and II), and a public dataset for external validation (n=127). We proposed a...

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Literature Corpus work: 537a510c-b712-5915-a192-54acdefe475e
DOI: 10.1101/2022.06.14.22276385

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