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人工智能在肺癌临床转化中的进展与挑战

Progress and challenges of artificial intelligence in lung cancer clinical translation.

作者信息

Zhu Erjia, Muneer Amgad, Zhang Jianjun, Xia Yang, Li Xiaomeng, Zhou Caicun, Heymach John V, Wu Jia, Le Xiuning

机构信息

Department of Thoracic/Head and Neck Medical Oncology, The University of Texas MD Anderson Cancer Center, Houston, TX, USA.

Department of Imaging Physics, The University of Texas MD Anderson Cancer Center, Houston, TX, USA.

出版信息

NPJ Precis Oncol. 2025 Jul 1;9(1):210. doi: 10.1038/s41698-025-00986-7.

Abstract

Artificial intelligence (AI) algorithms, such as convolutional neural networks and transformers, have significantly impacted cancer care. For lung cancer, AI holds great potential in addressing smoking cessation, personalized screening, and imaging genomics. And these data could be incorporated to optimize treatment selection. This review highlights the transformative impact of AI in lung cancer management, discusses crucial barriers such as model bias and fairness, and outlines future directions for clinical application.

摘要

人工智能(AI)算法,如卷积神经网络和变换器,对癌症治疗产生了重大影响。对于肺癌,人工智能在戒烟、个性化筛查和影像基因组学方面具有巨大潜力。这些数据可用于优化治疗选择。本综述强调了人工智能在肺癌管理中的变革性影响,讨论了模型偏差和公平性等关键障碍,并概述了临床应用的未来方向。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d3bd/12214742/c6bc06fee62f/41698_2025_986_Fig1_HTML.jpg

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