Artificial intelligence for autoimmune diseases
Emerging evidence suggests generative artificial intelligence (AI) may offer potential for autoimmune and rheumatic disease care, moving beyond traditional narrow AI applications to produce contextualized clinical content to support a wide spectrum of medical tasks. This article explores generative AI applications across autoimmune and rheumatologic clinical care, research, and administrative domains. However, significant implementation challenges remain, including clinical validation, model interpretability, data integration complexities, and evolving regulatory frameworks.
Authors
- Leland W.K. Chung (ORCID: https://orcid.org/0000-0003-0072-6939)
- Dylan Powell (ORCID: https://orcid.org/0000-0003-1233-5468)
- Avery LaChance (ORCID: https://orcid.org/0000-0001-7875-5284)
- Adam Rodman (ORCID: https://orcid.org/0000-0001-8452-0692)
- Arjun Mahajan
Institutions
- University of Stirling (GB)
- Brigham and Women's Hospital (US)
- Beth Israel Deaconess Medical Center (US)
- Harvard University (US)
- Stanford University (US)
Publication Details
- Journal
- npj Digital Medicine
- Published
- 2025-10-24
- DOI
- https://doi.org/10.1038/s41746-025-02015-0
- Citations
- 1
- Primary Topic
- Clinical Laboratory Practices and Quality Control
- Type
- article
- Field-Weighted Citation Impact
- 1.16