EQS Newswire: Hangzhou Diagens Biotechnology: Hong Kong Polytechnic University Joins Hands with Diagens Tech to Propel Medical AI into the Age of AI Agents

EQS Newswire / 04/09/2026 / 10:23 UTC+8

On 2 September, Diagens Technology Co., Ltd. (02526.HK, Diagens-B, "Diagens Tech") and Hong Kong Polytechnic University ("PolyU") jointly unveiled the PolyU - DIAGENS Joint Laboratory for Artificial General Intelligence and Medical Applications on PolyU's campus. It is learned that the two sides will carry out long-term cooperation on research and application of general artificial intelligence (AI) in healthcare. Priorities include medical image analysis, medical foundational models, and automation and AI empowerment of R&D workflows. They will explore new AI-powered approaches for medical research and connect research outcomes to innovation networks across Hong Kong, the Chinese mainland and the rest of the world.

Joint Lab for General AI and Medical Applications Officially Launched

Globally, AI technologies are evolving at a rapid pace, penetrating sectors at an accelerating rate. The integration of AI and healthcare has attracted widespread attention from all stakeholders.

On 2 September, the plaque of the Joint Lab for General AI and Medical Applications was unveiled on PolyU's campus, marking an accelerated boost for AI-healthcare integration.

The unveiling ceremony was officiated by Professor CHAO Yu Hang, PolyU's Senior Vice President (Research and Innovation), and Dr. SONG Ning, Founder and Chairman of the Board of Diagens Tech. Professor CHEN Changwen, Dean of PolyU's Faculty of Computer and Mathematical Sciences, Dr. LI Yongqi, Project Lead of the Joint Lab, together with representatives from PolyU's Research and Innovation Office, PolyU - Hangzhou Technology and Innovation Research Institute, and Diagens Tech attended the event.

In the 2025 ShanghaiRanking's Global Ranking of Academic Subjects, PolyU's AI discipline secured the No.1 spot in Hong Kong and 16th globally. Notably, AI was included in this global ranking for the first time, and PolyU claimed the top position locally - a testament to its leading role in AI education and research in Hong Kong.

AI is evolving from an assistive tool into an intrinsic part of scientific research and knowledge discovery, and medical AI is entering a new development phase. Professor Chao stated that China is pressing ahead with the Healthy China initiative. The establishment of this Joint Lab represents concrete actions by PolyU and Diagens Tech to respond to national strategic needs, seize technological opportunities and fulfil the social responsibilities of universities and enterprises. Combining PolyU's research strengths and Diagens Tech's industrial capabilities, the Joint Lab is expected to galvanize advances in medical AI and further improve the quality and efficiency of healthcare services in Hong Kong, across China and worldwide.

Dr. Song commented that AI for Science (AI4S) is reshaping the global medical AI landscape. AI presents challenges and opportunities comparable to the Apollo Program in helping humans decode life and health, and advance diagnosis, prevention and prediction of complex diseases. Diagens Tech has long strived to realize industrial-scale production of medical AI. Faced with explosive demand, neither enterprises nor universities can sustain global leadership alone. The Joint Lab with PolyU will deliver win-win empowerment by integrating PolyU's capacity for original innovation and Diagens Tech's industrial-scale delivery capabilities. It bridges academia and industry to explore new productivity paradigms for medical AI and usher in the next era of medical AI for Science.

Diagens Tech has long specialized in medical imaging AI foundational technologies and R&D-production systems, with a persistent focus on medical AI4S. It has achieved a major technological leap in medical AI, moving from one model per disease to industrialized mass production. Diagens Tech has developed the world's first and only foundational medical imaging model iMedImage, the intelligent image annotation platform iMedStudio, and dedicated model training and delivery platform iMedMaaS, creating an end-to-end value chain covering data generation, model development and deployment optimization.

As of H1 2026, Diagens Tech has collaborated with 99 hospitals to train 158 vertical models spanning 43 human organs and 61 disease areas, validating the technical pathway for batch model training enabled by reuse of foundational capabilities.

PolyU is one of the world's leading academic institutions. According to Dr. Song, the partnership marks a key milestone in Diagens Tech's long-term AI4S strategy. Building upon the Joint Lab, both parties will accelerate the development of the medical AI industry, advancing beyond large model development into the next phase of AI4S. This enables systematic research and scientific validation for more critical research topics sourced directly from clinical practice.

The Joint Lab to Drive Medical AI into the Age of AI Agents

Dr. Li, Project Lead of the Joint Lab, explained that traditional medical diagnosis and treatment relied entirely on clinicians' expertise accumulated over decades, leading to extremely long talent incubation cycles. Following AI-healthcare integration, academia and industry are eager to accelerate AI adoption in drug discovery, clinical care and healthcare administration. This will drive the transformation of the healthcare industry while benefiting public health. Medical AI may well become the highest-value vertical industry for AI deployment in the future. He noted that AI-healthcare integration is now at a critical inflection point of technological paradigm shift, having gone through two developmental stages.

The first stage is the small-model phase: teams collect targeted data and train dedicated small models for a specific disease or medical task, a process that often takes years. Dr. Li commented: "Small models remain necessary, yet they suffer from long development cycles and high costs. There are over 5,000 medical imaging detection tasks globally awaiting solutions, which calls for a new productivity paradigm."

The second stage is the large-model phase: a medical foundational model with general capabilities is pre-trained and then adapted for different diseases, datasets and medical tasks. This represents substantial progress compared with the first phase. For instance, general large models can cut the development cycle of specialty-specific models down to several months, while very few healthcare players possess such technology, capabilities and practical experience. After research on global medical AI players, Dr. Li found that most players are still building specialty-specific small models typical of Stage One. Diagens Tech's foundational medical imaging model iMedImage is globally leading, marking a breakthrough from Stage One to Stage Two. It transforms medical AI from "one model per disease" to "one foundation for thousands of models", delivering large-model-based industrialized mass production. This motivated him to partner with Diagens Tech to establish the Joint Lab and build a collaborative team.

What are the lab's objectives? According to Dr. Li, the Joint Lab aims to advance AI-healthcare integration into Stage Three: the age of AI Agents. In the large-model stage, substantial manual work is still required for data curation, parameter configuration, model training, result analysis and iterative refinement when adapting medical foundational models into specialty-specific models. He intends to combine Diagens Tech's expertise in medical large models and industrial deployment with PolyU's research strengths in large models, multimodal technology and AI Agents. The goal is to move medical AI beyond the large-model stage into the age of AI Agents: shifting from humans directly building specialty-specific small models on general large models, to humans training AI Agents to develop specialty-specific small models based on foundational large models.

What role will AI play in the AI Agent era? Dr. Li explained that for research and innovation, the lab will explore how AI agents can participate in the full lifecycle of medical AI R&D: interpreting research tasks, invoking specialist tools, running model experiments, analyzing outputs and iterating research plans based on feedback. This enables AI to evolve beyond single-task execution to support researchers conducting continuous, systematic medical studies. PolyU excels at frontier AI research, while Diagens Tech owns medical foundational models, R&D platforms and real-world deployment scenarios. The collaboration frames research around practical clinical challenges and validates new technologies within real-world settings. It shortens the path from academic inquiry to operational systems and products, allowing research outcomes to benefit clinical practice faster and more effectively.

Medical AI stands as one of the most critical and representative fields of AI for Science. Its development is essentially a story of advancing AI technologies unlocking greater productivity in medical R&D. Dr. Li noted that the lab's ambition is not merely improving individual models, but building a generative, replicable and scalable paradigm for medical AI R&D. This unlocks solutions for medical challenges once understudied due to high costs and long timelines, ushering in a new productivity era for the medical AI sector.

Linking Research Outcomes to Innovation Networks in Hong Kong, Chinese Mainland and Rest of the World

Leveraging Hong Kong's international innovation ecosystem and PolyU's research networks, both parties will further connect with healthcare institutions, research teams and industry partners across the Chinese mainland and worldwide. They will facilitate international academic exchange and validation of research findings, bringing clinical challenges, datasets and research methodologies originating from Chinese healthcare practice into broader global scientific collaboration.

Moving ahead, the Joint Lab will be grounded in real-world clinical needs to drive its research agenda. The two partners aim to tackle long-standing medical challenges, enable previously unfeasible research, and generate internationally influential original innovations. The collaboration will deliver cutting-edge technological and research support for the Healthy China initiative and global healthcare development.

04/09/2026 Dissemination of a Financial Press Release, transmitted by EQS News.
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