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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.
Rheumatic Diseases Clinics of North America
|July 6, 2026
Summary
Artificial intelligence (AI) is becoming a key part of rheumatology care, aiding in diagnosis and patient monitoring. Ensuring trustworthy AI implementation is crucial to maximize benefits while mitigating risks in patient treatment.
Area of Science:
- Clinical applications of artificial intelligence (AI).
- Rheumatology and patient care.
- Biomedical research and clinical integration.
Background:
- Artificial intelligence (AI) is increasingly integrated into clinical tools within rheumatology.
- AI is transitioning from research to operational use in electronic health records, imaging, and decision support systems.
- Rheumatology's longitudinal care model presents unique opportunities and risks for AI implementation.
Purpose of the Study:
- To explore the integration of AI in rheumatology clinical practice.
- To identify the promise and risks associated with AI in rheumatology.
- To outline a framework for operationalizing trustworthy AI systems in patient care.
Main Methods:
- Review of current AI applications in rheumatology.
- Analysis of AI's role in imaging, disease monitoring, and decision support.
- Discussion of ethical considerations and implementation strategies for trustworthy AI.
Main Results:
- AI is actively being embedded in various rheumatology clinical tools.
- Significant potential exists for AI to improve rheumatologic care delivery.
- Distinct risks associated with AI in rheumatology require careful management.
Conclusions:
- Trustworthy artificial intelligence (AI) systems are essential for responsible integration in rheumatology.
- A framework encompassing ethical commitments operationalizes trustworthy AI across patient care.
- Balancing innovation with risk management is key for AI's future in rheumatology.
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