On December 20, the "Intelligent Computing Synergy in Healthcare: Ecosystem Linking the Future" themed seminar was held in Chengdu. Lenovo Group, together with ecosystem partners like Intel, clients, and media representatives, visited Xunshang Healthcare to discuss innovative applications of intelligent computing technology in AI+ healthcare.

Lenovo Group has been actively expanding its presence in AI+ healthcare, having developed a scenario-based smart healthcare solution centered on "AI large models + RPA + integrated platform" for Xunshang Healthcare. By establishing an enterprise-level integrated platform and Clinical Data Repository (CDR), Lenovo helps hospitals aggregate, manage, and standardize data scattered across multiple systems such as HIS, orders, and finance. This creates a unified "360-degree holographic patient view," enabling intelligent enhancements across patient treatment processes and internal operational management, achieving a leap from "data accumulation" to "data governance."

Huang Shan, Strategic Management Director of Lenovo China's Infrastructure Business Group, emphasized during the event: "Robust AI factory infrastructure and continuously evolving computing engines form the cornerstone for supporting smart healthcare applications and ensuring their stable, efficient operation. As a leading AI infrastructure provider, Lenovo is leveraging its technological capabilities to deliver truly 'usable' computing power to the healthcare sector, enabling broader access to high-quality medical resources."

Huang further explained that based on this solid data foundation, Lenovo has deployed its AI middleware and full lifecycle model management capabilities. This allows the "Xunshang AI Hospital" project to achieve continuous and agile model iteration. Lenovo's toolchain and platform support distillation training and targeted optimization of privately deployed large models (such as DeepSeek R1) based on specific knowledge bases, ensuring model capabilities keep pace with the latest developments in clinical practice and medical knowledge. This represents a shift from "one-time delivery" to "continuous evolution."