Artificial intelligence (AI) is rapidly reshaping thoracic surgery, advancing from decision support to the threshold of autonomous intervention. AI-driven technologies—including machine learning (ML), deep learning (DL), and computer vision—have demonstrated significant improvements in diagnostic accuracy, surgical planning, intraoperative navigation, and postoperative outcome prediction. In lung cancer and thoracic oncology, AI enhances imaging analysis, histopathological classification, and risk stratification, supporting multidisciplinary decision-making and personalized therapy. Robotic-assisted and AI-guided systems are optimizing surgical precision and workflow efficiency, while real-time decision-support tools and augmented reality are improving intraoperative safety. Despite these advances, widespread adoption is limited by challenges in algorithmic bias, data integration, regulatory approval, and ethical transparency. The literature emphasizes the need for multicenter validation, explainable AI, and robust governance frameworks to ensure safe and effective clinical integration. Future research should focus on digital twin technology, federated learning, and transparent AI outputs to further enhance reliability and accessibility. AI is poised to transform thoracic surgery, but responsible implementation and ongoing evaluation are essential for realizing its full potential. The aim of this review is to evaluate and synthesize the current landscape of artificial intelligence (AI) applications across the thoracic surgical pathway, from preoperative decision-support to intraoperative guidance and emerging autonomous interventions.
人工智能正在重塑胸外科领域，其应用已从决策支持发展到接近自主干预的临界点。以机器学习、深度学习和计算机视觉为代表的AI驱动技术，在诊断准确性、手术规划、术中导航及术后预后预测方面展现出显著优势。在肺癌与胸部肿瘤领域，AI通过提升影像学分析、组织病理学分型及风险分层能力，有力支持多学科决策与个体化治疗。机器人辅助与AI引导系统正优化手术精准度与工作流效率，而实时决策支持工具与增强现实技术则提升了术中安全性。尽管成果显著，但算法偏差、数据整合、监管审批及伦理透明度等挑战仍限制其广泛应用。文献强调需要通过多中心验证、可解释人工智能及健全治理框架确保临床转化的安全性与有效性。未来研究应聚焦数字孪生技术、联邦学习及透明化AI输出，以进一步提升系统可靠性与可及性。人工智能必将变革胸外科实践，但负责任的应用与持续评估是实现其全部潜力的关键。本文旨在系统评述人工智能在胸外科诊疗全路径中的应用现状，涵盖术前决策支持、术中导航及新兴自主干预技术。
肿瘤(癌症)患者之家