HK Stock Market Move | RIMAG GROUP (02522) surged more than 6% in early trading, and HE Yi Medical's global debut of the large model product AIR, a medical imaging platform.

RIMAG GROUP (02522) rose more than 6% in the morning session, rising 6.23% to HK$17.23 by the time of publication, with a turnover of HK$80.62 million. In terms of news, RIMAG GROUP announced that on October 16, 2025, Shanghai Yinghe Medical Maimai Intelligent Technology Co., Ltd. (Yinghe Medical Maimai), a joint venture incubated by the group in the field of artificial intelligence, officially launched the world's first AI-assisted diagnostic product based on a medical image pedestal large model "Yinghe Miaoya" - chest CT plain scan assisted diagnosis AIR. The AIR product marks the official transition of medical image AI from the "single disease small model" 1.0 era to the "pedestal large model-driven" 2.0 era, with the ability to diagnose all lesions, all diseases, and multiple organs in a coordinated manner, representing a milestone breakthrough in the field of intelligent medical imaging diagnosis. The AIR product is based on the scan site as the diagnostic unit, with the first landing product focusing on chest CT plain scans, achieving simultaneous detection and diagnosis of all lesions of the lungs, pleura, and mediastinum, covering all common diseases in this area. The AIR product is developed based on the world's first cross-modal, all-process medical image pedestal large model "Yinghe Miaoya", with the ability to segment multiple organs in a coordinated manner, fully reflecting its technical advantages of efficient diagnosis, precise coverage, interactive coordination, and seamless integration, fundamentally reconstructing the research and application logic of medical image AI. The AIR product is not only a diagnostic tool, but also the first commercialized result of the Yinghe Medical Maimai pedestal large model ecosystem. By connecting top hospitals with grassroots medical institutions through open interfaces, it creates a positive cycle of "data feedback model iteration, model-driven scene landing". This model significantly shortens the AI product development cycle, reduces development costs, helps medical institutions achieve screening standards, intelligent diagnosis, and universal service, effectively promotes industry chain collaboration, and constructs a "data-model-scene" closed-loop ecosystem.