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Researchers from the ADAPT Centre in the Schools of Medicine and Computer Science and Statistics at Trinity College Dublin, in collaboration with colleagues at Lund University, have made a major breakthrough in vasculitis research. Their findings, recently published in The Lancet Rheumatology, provide new insights into the diagnosis and treatment of systemic vasculitis, a group of rare and complex autoimmune diseases.
The study, part of the FAIRVASC project, leverages advanced artificial intelligence (AI) and big data technologies to address key challenges in the diagnosis and treatment of systemic vasculitis. FAIRVASC connects vasculitis patient registries across Europe, enabling seamless data sharing and advanced analytics to advance research and improve patient care.
This study focuses on antineutrophil cytoplasmic antibody (ANCA)-associated vasculitis and introduces a novel approach to classify this disease using a federated dataset that is 10 times larger than previous studies.
“Access to this much larger dataset enabled more in-depth analysis, revealing previously unidentified disease clusters. This new classification method allows for more accurate prediction of outcomes such as overall survival and kidney health, paving the way for more personalized treatment strategies that can significantly enhance patient care.”
Professor Mark Little, Professor of Nephrology and Kidney Specialist at Tallaght and Beaumont Hospital, Trinity College Dublin, said: “Our study shows that by leveraging advanced AI systems and a wide dataset, we can discover new patterns in this rare autoimmune disease that influence the likelihood of adverse outcomes. This could allow us to target potentially toxic treatments to patients most likely to benefit.”
“Such progress is only possible through a multidisciplinary approach and direct involvement of patients with the lived experience of the disease, and this collaborative project has succeeded in bringing together experts in medicine, computer science and statistics.”
Professor Declan O'Sullivan, ADAPT Principal Investigator and Professor of Computer Science at Trinity, said: “We are pleased to see that our group's research focus – knowledge graphs for data integration – is having an impact on the advancement of medical research, particularly in the integration of rare disease patient registries.”
This study highlights the transformative potential of AI in medical research, particularly in addressing the complexities of rare diseases, where it has previously been impossible to generate large enough cohorts to enable meaningful research.
By enabling them to more accurately identify disease patterns, AI is revolutionizing how clinicians approach diagnosis and treatment, offering hope for better outcomes not only for vasculitis patients, but also for those suffering from other rare and hard-to-treat diseases.
This research serves as a blueprint for leveraging advanced technologies to address similar challenges in the broader rare disease field, potentially leading to breakthroughs that could benefit countless patients around the world.
Further information: Karl Gisslander et al. “Data-driven subclassification of ANCA-associated vasculitis: model-based clustering of a coalition international cohort.” The Lancet Rheumatology (2024). DOI: 10.1016/S2665-9913(24)00187-5
Courtesy of Trinity College Dublin
Source: AI-powered big data research advances understanding of systemic vasculitis (August 27, 2024) Retrieved August 27, 2024 from https://medicalxpress.com/news/2024-08-ai-powered-big-vasculitis.html
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