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The Hong Kong Hub of Obstetric and Paediatric Excellence (HOPE) at The Chinese University of Hong Kong (CUHK) and Hangzhou Diagens Biotechnology Co., Ltd. (Diagens) signed a Memorandum of Understanding (MoU) recently. Focusing on the field of maternal and child healthcare, both parties will jointly advance innovative research on medical artificial intelligence (AI) imaging foundation models, with an aim to translate medical AI technologies into clinical applications, and further enhance the quality of diagnosis and treatment for women and children.

The MoU was signed by Professor Leung Tak-yeung, Co-Director of HOPE; Assistant Dean (Mainland Affairs) and Professor in the Department of Obstetrics and Gynaecology, CUHK’s Faculty of Medicine (CU Medicine); and Dr Song Ning, Founder and Chairman of Diagens. Leveraging HOPE’s clinical and research prowess and Diagens’ technical expertise in AI, the collaboration will encompass academic research, specialised model training, clinical translation and validation, the development of AI evaluation systems, and talent and academic exchange.

Professor Leung remarked: “This collaboration extends beyond a paper agreement. It establishes a long-term mechanism designed to bridge clinical needs with frontier AI technologies. We look forward to working with Diagens to transform research outcomes into practical applications that serve the maternal and child healthcare needs of the Greater Bay Area, while maintaining the highest standards of ethics and data security.”

Dr Song added: “CUHK is a world-class research university with profound clinical expertise and academic influence. For Diagens, this partnership marks a significant milestone in transitioning our medical imaging foundation models from R&D to sophisticated clinical implementation. We envisage a joint exploration of a sustainable path from scientific discovery to clinical application.”

Under the MoU, the two parties will align on initial joint research projects, with a focus on medical imaging AI for maternal and child health, specialised model development, assisted diagnosis, and clinical validation. Subject to regulatory compliance, they will also explore pathways to support healthcare development across the Greater Bay Area.