Seoul National University Bundang Hospital is embarking on a project to develop a 'full-stack medical AI' model that connects the entire patient journey through artificial intelligence (AI). The hospital is participating in the Ministry of Science and ICT's 'AX-Ready pilot project,' which aims to integrate AI across various aspects of healthcare, from clinical support to regional collaboration and hospital automation.
On July 16, the hospital held a kickoff meeting for the AX-Ready pilot project in its main conference room, officially launching the 'AICON (AI Connected Care Operating Network),' a comprehensive medical AI operational network based on the entire patient journey.
This initiative arises from the recognition that, despite the rapid growth of medical AI in South Korea, its application in hospital settings remains limited. As of the first quarter of 2026, the Ministry of Food and Drug Safety has approved a total of 549 medical AI products. However, varying levels of information technology capabilities and implementation conditions across hospitals have led to concerns about the high costs and trial-and-error burdens associated with piecemeal solutions.
The AX-Ready pilot project aims to overcome these limitations by creating a model for the strategic national use of medical AI. The focus is on seamlessly integrating AI into the entire patient care process while addressing regional healthcare and essential medical crises.
The AICON consortium includes 21 organizations, such as Seoul National University Bundang Hospital, Seoul National University Hospital, the National Medical Center, the Central Veterans Hospital, Seongnam Medical Center, local clinics, and various medical IT and AI companies like EasyCareTech, Kakao Healthcare, Bit Computer, Acryl, and Puzzle AI, as well as academic institutions like Seoul National University. This diverse collaboration encompasses the entire healthcare system, from advanced general hospitals to local medical facilities and technology firms.
The pilot will be implemented in three packages. The first package involves clinical support AI that connects ten commercially available medical AI products approved by the Ministry of Food and Drug Safety for diagnosis, management, and prognosis prediction. The second package includes a collaborative platform that supports referrals and returns between local medical institutions, featuring a patient-facing 'CareNavi' and a healthcare provider-oriented 'CarePilot,' along with an AI collaboration agent. The third package focuses on hospital automation systems that implement smart wards through nine solutions, including voice-based medical record automation, fall detection, and emergency room AI agents.
Another notable aspect of this project is its emphasis on standardization. By establishing a common platform based on the KR-Core FHIR healthcare data standard and the MCP AI integration standard, the initiative aims to create a structure where multiple institutions can share a single AI system, rather than developing separate systems for each hospital. This approach is expected to significantly reduce barriers to implementation and costs compared to the previous method of customizing solutions for different environments.
The project will also produce standardized assets, including a six-step onboarding manual, an AI utilization maturity assessment framework, and a security and ethics governance system, all of which will be made publicly available. Seoul National University Bundang Hospital aims to establish a practical diffusion model that any hospital can utilize, laying the groundwork for the nationwide expansion of AI-specialized hospitals.
Jeon Young-tae, the president of Seoul National University Bundang Hospital, stated, "While existing medical AI technologies have focused on interpreting specific diseases, AX-Ready represents a full-stack medical AI integration model that connects the entire patient journey. We aim to demonstrate that AI is not just a technology for its own sake, but one that leads to patient safety and improved treatment outcomes."
* This article has been translated by AI.
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