Rheumatology study offers AI insights into autoimmune diseases

New research from Trinity College Dublin has provided evidence for improved diagnosis and treatment of rare diseases, the authors of a recent rheumatology study have said.

 

Researchers from the School of Medicine and the ADAPT Centre at the School of Computer Science and Statistics at Trinity College Dublin have made a significant breakthrough in vasculitis research, in collaboration with researchers in Lund University.

 

Their findings, which were published in The Lancet Rheumatology recently, offer new insights into the diagnosis and treatment of systemic vasculitis, a group of rare and complex autoimmune diseases.

 

The study, part of the EU-funded FAIRVASC project, leveraged advanced artificial intelligence (AI) and big data techniques to address critical challenges in diagnosing and treating systemic vasculitis.

 

FAIRVASC connects vasculitis patient registries across Europe, enabling seamless data sharing and advanced analysis to drive forward research and improve patient care.

 

Focusing on antineutrophil cytoplasm antibody (ANCA)-associated vasculitis, the research introduced a novel approach to classifying this disease using a federated dataset ten times larger than previous studies.  

 

Access to this much larger dataset enabled more detailed analysis, revealing previously unidentified disease clusters. It is hoped this new classification method will offer more accurate predictions of outcomes like overall survival and kidney health, paving the way for more personalised treatment strategies that can significantly enhance patient care.