Chinese research team develops AI-powered diagnostic system for rare diseases

中国研究团队研发出针对罕见病的AI辅助诊断系统

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2026-03-13

12 分钟
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1. Chinese research team develops AI-powered diagnostic system for rare diseases. 2. China achieves breakthrough in high-orbit satellite-ground laser communication. 3. China ramps up financial support for tech innovation: senior official. 4. China's foreign trade records strong start to 2026 with double-digit growth.
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  • The world is changing fast that you can learn it at a slower pace.

  • Special English Please note that the following stories are read by AI,

  • but all information has been written and verified by professional editors.

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  • A Chinese research team has developed an AI-powered rare disease diagnostic system called DeepRare,

  • setting a new record for diagnostic accuracy.

  • The study has been published in the journal Nature.

  • The diagnosis and treatment of rare diseases have long faced challenges in confirming cases without genetic testing,

  • particularly in regions with limited access to such services.

  • Meanwhile,

  • traditional medical AI diagnostic systems often encounter trust issues due to their non-traceable reasoning processes.

  • The evidence-based DeepRare was developed by a team from Xinhua Hospital affiliated with the Shanghai Jiao Tong University's School of Medicine and the University's School of Artificial Intelligence

  • since its online diagnostic platform was launched last July.

  • It has registered over 1,000 professional users across more than 600 medical and research institutions worldwide.

  • Test data show that when only patients' clinical phenotypic information was provided without genetic data,

  • DeepRARE achieved a first attempt accuracy of 57% in phenotypic diagnosis,

  • an improvement of nearly 24 percentage points over the previous global model.

  • When genetic data were incorporated, its diagnostic accuracy exceeded 70%.

  • according to the study.

  • DeepRARE integrates real-time access to a vast repository of medical literature knowledge and real-world clinical case data.