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中华胸部外科电子杂志 ›› 2026, Vol. 13 ›› Issue (01) : 64 -73. doi: 10.3877/cma.j.issn.2095-8773.2026.01.07

综述

人工智能在肺结节诊疗体系中的应用前景
杜昊楠1, 张广健1, 王嘉巍1, 梁挺2, 锁瑞洋2, 张佳1,()   
  1. 1710061 西安,西安交通大学第一附属医院胸外科
    2710061 西安,西安交通大学第一附属医院医学影像科
  • 收稿日期:2025-04-17 修回日期:2025-06-22 接受日期:2026-02-06 出版日期:2026-02-28
  • 通信作者: 张佳

Application prospects of artificial intelligence in the diagnosis and treatment of pulmonary nodules

Haonan Du1, Guangjian Zhang1, Jiawei Wang1, Ting Liang2, Ruiyang Suo2, Jia Zhang1,()   

  1. 1Department of Thoracic Surgery, First Affiliated Hospital of Xi’an Jiaotong University, Xi’an 710061, China
    2Department of Radiology, First Affiliated Hospital of Xi’an Jiaotong University, Xi’an 710061, China
  • Received:2025-04-17 Revised:2025-06-22 Accepted:2026-02-06 Published:2026-02-28
  • Corresponding author: Jia Zhang
引用本文:

杜昊楠, 张广健, 王嘉巍, 梁挺, 锁瑞洋, 张佳. 人工智能在肺结节诊疗体系中的应用前景[J/OL]. 中华胸部外科电子杂志, 2026, 13(01): 64-73.

Haonan Du, Guangjian Zhang, Jiawei Wang, Ting Liang, Ruiyang Suo, Jia Zhang. Application prospects of artificial intelligence in the diagnosis and treatment of pulmonary nodules[J/OL]. Chinese Journal of Thoracic Surgery(Electronic Edition), 2026, 13(01): 64-73.

肺结节的早期诊疗仍面临影像学误判、定位不准确及术后评估困难等技术瓶颈。人工智能(AI)技术在术前评估、术中导航和术后监测等方面的应用,逐步为突破上述难题提供了新的解决方案。术前,AI模型显著提升了结节识别与风险分层的准确性;术中,通过融合虚拟现实、增强现实与机器人辅助手术技术,AI有助于术式规划并提高手术操作的稳定性;术后,基于AI的预测模型支持对并发症与复发风险的动态评估,推动了精准康复策略的构建。本文综述了AI在肺结节外科手术中的最新进展,旨在为未来技术演进与临床实践的融合提供参考。

The early diagnosis and treatment of pulmonary nodules still faces technical challenges, such as imaging misdiagnosis, inaccurate localization, and difficulties in postoperative evaluation. The application of artificial intelligence (AI) in preoperative assessment, intraoperative navigation, and postoperative monitoring has gradually provided new solutions to address these issues. Preoperatively, AI models significantly improve the accuracy of nodule recognition and risk stratification; intraoperatively, through the integration of virtual reality, augmented reality, and robot-assisted surgery techniques, AI enhances surgical planning and operative stability; postoperatively, AI-based predictive models enable dynamic assessment of complications and the risk of recurrence, promoting the development of personalized rehabilitation strategies. This review summarizes the latest advances in AI applications in pulmonary nodule surgery, aiming to provide insights for the integration of future technological advancements with clinical practice.

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