https://english.news.cn/20260220/bc76e1aa654b4eb1b21f67073236d8ff/c.html
https://www.nature.com/articles/s41586-025-10097-9
Rare diseases affect more than 300 million people worldwide. Patients often endure a prolonged ‘diagnostic odyssey’ exceeding 5 years, marked by repeated referrals, misdiagnoses and unnecessary interventions, leading to delayed treatment and substantial emotional and economic burden.
A research team at Xinhua Hospital, an affiliated hospital of Jiao Tong hospital in Shanghai, has developed an AI-powered rare disease diagnostic system called DeepRare. 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.
The research team plans to complete real-world validation of 20,000 rare disease cases within the next six months.