Supported by big data, knowledge graph, search expansion generation and multi-agent technology, Shanghai has significantly strengthened its capacity for public health risk identification, intelligent early warning and precise intervention, demonstrating solid progress in China’s intelligent public health development, local health officials said at the International Health Conference in Switzerland.
As an important side event to the 79th World Health Assembly, the international conference “Smart Healthcare and Health Systems Innovation: Artificial Intelligence to Enabling Human-Centered, Integrated Digital Health” convened experts from 62 countries, including the World Health Organization, world-leading universities, national health authorities, and leading healthcare companies, to explore the innovative role of artificial intelligence in advancing integrated digital health.
According to Shanghai CDC Director Chen Xin, the framework is backed by a dual-base infrastructure. One is a data platform that aggregates 42 systems to build a high-quality, multimodal public health corpus, and the other is an AI computing backbone that supports multi-agent collaboration and vertical-specific large-scale language models. This foundation enables you to transform complex public health workflows into scalable, AI-driven solutions.
Shanghai CDC has gone beyond infectious disease surveillance to develop AI-powered population health services that span the entire lifecycle. The system is tailored for adolescents, working-age adults, and older adults and employs three intelligent agents: a label annotation tool for high-quality data governance, a digital twin cohort model to simulate health evolution, and personalized health assessment and intervention services. The mobile application supports chronic disease management through interactive health portraits and dynamic risk assessments, and provides customized guidance and community care referrals through search augmented generation (RAG) technology.
International experts also shared their exploration of cutting-edge technologies in clinical practice. Olivier Michelin, Head of the Oncology Department at Geneva University Hospital, elaborated on AI applications in precision oncology. He pointed out that artificial intelligence can integrate clinical data, multi-omics data, digital pathology and spatial-omics data, breaking the limitations of traditional one-size-fits-all diagnostic and treatment models. This technology enables personalized cancer treatment and brings new therapeutic hope to cancer patients around the world.
The advanced implementation of AI has brought remarkable results in lung nodule screening, lung cancer image interpretation, and pathological diagnosis at Shanghai Lung Hospital, said Deputy Director Tao Rong.
He noted that while the biggest hurdle currently lies in legally and compliantly sharing medical data within hospitals, ethical concerns are also hindering the promotion of related technologies among hospitals.
Wang Dahui, vice president of Fudan University Children’s Hospital, pointed out that the management of pediatric medical supplies is plagued by insufficient data, vague accountability, and isolated information systems. He proposed addressing these challenges by adhering to the principles of AI-assisted decision-making and establishing data sharing alliances and layered service platforms.
Industry stakeholders said that large-scale deployment of medical AI is limited by poor connectivity of data, medical services, and payment systems, and emphasized the need to develop medical AI-specific evaluation standards to enable effective dialogue between healthcare professionals and service users.
Luo Li from Fudan University’s School of Public Health emphasized that the application of AI in the health field is a global cause that transcends regional boundaries. He advocated a dialectical and rational view of artificial intelligence, fully recognizing its enormous potential while avoiding the risks arising from inappropriate application of the technology. Mr. Luo emphasized that a sound institutional framework is urgently needed to regulate and guide the healthy development of AI.
“In the health sector, which is closely related to public welfare, human-centered principles must always be observed to ensure that AI technologies enable high-quality human health development,” he said.
