Artificial intelligence for autoimmune diseases

Le résumé fourni par la source

Research suggests nearly one in ten individuals is affected by an autoimmune or rheumatic disease – conditions that largely lack definitive cures and show a rapidly rising incidence 1 , 2 . In light of these pressing challenges, recent npj Digital Medicine articles highlight how recent developments in artificial intelligence, particularly in generative artificial intelligence (GenAI), represent a potential paradigm shift in autoimmune and rheumatic disease care 3 , 4 , 5 . Traditional AI applications for rheumatic diseases have mainly focused on narrow tasks, like classification or prediction 6 . In contrast, generative models, such as large language models (LLMs), can produce contextualized clinical content and recommendations informed by large medical datasets, supporting a wide range of clinical tasks 6 , 7 . These models may be particularly valuable for rheumatologic practice, which is often defined by diagnostic uncertainty, varied disease presentations, and the need for individualized treatment 8 , 9 . Despite this alignment, the applications of this technology across autoimmune and rheumatologic clinical care, research, and administrative workflows remain largely unexplored.

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