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

Source: Xinhua

Editor: huaxia

2026-02-20 18:41:00

SHANGHAI, Feb. 20 (Xinhua) -- A Chinese research team has developed an AI-powered rare disease diagnostic system called DeepRare, setting a new record for diagnostic accuracy, according to a study published Thursday 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 (SJTU) School of Medicine and SJTU 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 57.18 percent 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 percent.

According to the study, DeepRare integrates real-time access to a vast repository of medical literature knowledge and real-world clinical case data. In terms of diagnostic reasoning, it employs an iterative cycle of hypothesis, verification and self-reflection to evaluate diagnostic clues and correct logical gaps.

Regarding the reasoning process, each diagnostic conclusion comes with a complete chain of evidence, allowing doctors not only to see the diagnosis but also to understand the underlying basis.

Sun Kun, one of the corresponding authors of the paper from Xinhua Hospital, said that the research team is preparing to initiate a global AI alliance for rare disease diagnosis and treatment.

They plan to complete real-world validation of 20,000 rare disease cases within the next six months, he added.