Researchers from China have developed a new artificial intelligence tool designed to address a major challenge in medicine: rare diseases. Called DeepRare, the AI-powered tool has been demonstrated to accelerate and improve the diagnosis of rare diseases in a study published on Feb. 18 in the international journal Nature.
What Are Rare Diseases And The Challenges Behind Them?
Rare diseases are defined as conditions affecting fewer than 1 in 2,000 people, which collectively impact over 300 million people worldwide, according to the study researchers. More than 7,000 distinct rare disorders exist, with about 80% having genetic origins.
These conditions are notoriously hard to diagnose due to their diverse symptoms, low prevalence, and limited clinician expertise, often leaving patients waiting for years — sometimes more than five — for an accurate identification. Traditional approaches, such as newborn whole-genome sequencing, have advanced the field but require specialised knowledge and can overwhelm healthcare providers with vast data.
How Does DeepRare AI Help In Rare Disease Diagnosis?
DeepRare overcomes these challenges by employing a large language model at its core, integrated into an agentic framework. Its architecture reportedly incorporates over 40 AI agents and tools that handle distinct tasks. These include extracting symptoms from notes, matching symptoms with diseases, searching medical literature for similar cases, and analysing genetic variants from sequencing data.
The tool processes inputs to generate a list of ranked diagnoses. Crucially, it provides transparent information backed by verifiable references from medical sources, reducing the need for extensive manual literature reviews.
DeepRare AI Beat Experienced Clinicians In Testing
In testing on 6,401 cases, DeepRare demonstrated strong results. It showed performance that was better than 15 existing diagnostic tools. When incorporating genetic data, it could accurately diagnose 69% of patients in one study cohort and surpassed popular tools like Exomiser (around 56%). Researchers surmised that DeepRare had the potential to accurately diagnose a disease much earlier.
The bigger achievement of the AI tool involved 163 challenging real-world cases. DeepRare correctly identified the disease on its first attempt in 64.4% of instances, compared to 54.6% for five experienced clinicians — each with over a decade in rare disease practice. Overall, it succeeded in about 79% of cases versus 66% for the experts.
“The clinical implications of DeepRare extend beyond diagnostic accuracy to address fundamental challenges in rare disease care delivery,” the researchers wrote in their study.
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