人工智能驱动肺癌诊疗:研究进展与未来展望OA

Lung cancer,the malignancy with the highest global mortality rate,is currently undergoing a paradigm shift from precision medicine to intelligent medicine in its diagnostic and therapeutic models.Arti-ficial intelligence(AI),leveraging its core advantages in multimodal data fusion and high-dimensional feature extraction,has deeply permeated the entire disease continuum of lung cancer screening,diagnosis,and indi-vidualized treatment.AI demonstrates significant value in improving patient outcomes and enhancing clinical ef-ficiency,thereby reshaping the fundamental logic and clinical practice pathways of lung cancer management.This article reviews the latest advances of AI in real-world clinical diagnosis and treatment scenarios for lung cancer,with a focus on multimodal data fusion architectures,breakthrough applications of AI-assisted lung cancer diagnosis and treatment,and the practical barriers to clinical translation.It critically analyzes core chal-lenges including data standardization,privacy protection,and ethical compliance.Finally,it envisions the fu-ture landscape of a nationwide intelligent ecosystem for lung cancer diagnosis and treatment—driven by federated learning and empowered by data elements—providing a reference for the standardized application and innovative development of AI in precision lung cancer care.