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Artificial Intelligence Regulation in the United States: Current Landscape and Implications for Rheumatology
1Division of Immunology and Rheumatology, Department of Medicine, Stanford University School of Medicine, Stanford, CA 94305, USA; Center for Population Health Sciences, Stanford University, Stanford, CA 94305, USA; Department of Veterans Affairs, Program Evaluation Resource Center, Office of Mental Health, Menlo Park, CA 94025, USA.
Abstract:
Artificial intelligence (AI) is increasingly embedded in clinical tools used in rheumatology, including imaging interpretation, longitudinal disease monitoring, and electronic health record-based decision support. AI has moved from the periphery of biomedical research to an operational component of clinical care, increasingly embedded in electronic health records, imaging platforms, and decision support systems. In rheumatology, where care is longitudinal, AI systems offer substantial promise-but also poses distinct risks. Together, these commitments-advancing humanity, ensuring equity, engaging impacted individuals, improving workforce well-being, monitoring performance, innovating and learning, and promoting sustainability-operationalize trustworthy AI systems across a patient's care trajectory.
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