影像组学与深度学习在胃癌预后及疗效评价的研究进展

Research Progress of Radiomics and Deep Learning in the Prognosis and Efficacy Evaluation of Gastric Cancer

影像组学和深度学习是如今热门的研究方法,在肿瘤的诊断、鉴别诊断、分型、治疗反应及预后等方面已初步显示出重要作用。本文旨在介绍影像组学的工作流程及深度学习的基本概念,并综述其在胃癌预后和疗效评价中的应用进展,对现有研究的成果以及未来的研究挑战和发展机遇进行总结,以期为临床对胃癌的精准诊疗提供价值。

Radiomics and deep learning are popular research methods,which have initially shown important roles in the diagnosis,differential diagnosis,classification,treatment response and prognosis of tumors.The purpose of this paper is to introduce the workflow of radiomics and the basic concepts of deep learning,and review the application progress of radiomics in the prognosis and efficacy evaluation of gastric cancer,and summarize the existing research results,research challenges and development opportunities in the future,in order to provide value for the precise diagnosis and treatment of gastric cancer in clinical practice.