数智化诊疗技术在消化内镜外科中创新应用与临床实践OA

Digestive endoscopic surgery is undergoing a transformative leap driven by"digital intelligence",where the deep integration of artificial intelligence(AI),robotics,cloud-based big data,and large language models(LLMs)is reshaping the paradigm of minimally invasive diagnosis and treatment.In diagnostics,the deployment of computer-aided detection(CADe)and computer-aided diagnosis(CADx)has significantly improved lesion detection rates and the consistency of optical characterization,establishing a closed loop for real-time quality control.In therapeutics,flexible endoscopic robots-leveraging multi-channel collaborative control,wristed instrumentation,and kinematic enhancement-have effectively overcome the physical limitations of traditional endoscopy regarding traction,stability,and suturing.These advancements not only lower the technical threshold and complication risks associated with complex endoscopic procedures but also expand the therapeutic boundaries of endoscopic surgery.Concurrently,the integration of cloud-network convergence and multi-modal big data dismantles information silos,providing a robust foundation for remote collaboration,standardized training,and real-world studies,with data governance adhering to FAIR principles serving as a critical pillar.Furthermore,LLMs combined with Retrieval-Augmented Generation(RAG)demonstrate substantial potential in clinical decision support,automated reporting,and patient education.Although challenges persist regarding model generalization,workflow integration,alarm fatigue,cost-effectiveness,and data privacy/compliance,future advancements focusing on multi-center validation,interpretability,uncertainty quantification,optimized human-machine interfaces,and value-based payment and regulatory frameworks will continue to propel digestive endoscopic surgery toward safe,widespread,and homogenized clinical practice.