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Big data analytics and processing through artificial intelligence (AI) are increasingly being used in the health sector. This includes both clinical and research settings, and newly in specialties like rheumatology. It is, however, important to consider how these new methodologies are used, and particularly the sensitivities associated with personal information. The use of big data and AI processing in healthcare has great potential to improve the quality of clinical care, including through better diagnosis, treatment, and prognosis. They may also increase patient and societal participation and engagement in healthcare and research. Developing these methodologies and using the information generated from them in line with ethical standards could positively affect the design of global health policies and introduce a new phase in the democratization of health.

How can we help?

Our current applications of big data, data analytics, and AI in rheumatology—including registries, machine learning algorithms, and consumer-facing platforms
Our Machine learning and big data aid diagnosis, treatment, and prognosis, can help rheumatology specialists to maintain the promise of fiduciary obligations in the physician–patient relationship.
We can set up data collaboration in big data projects and increased patient engagement in ways to counteract health inequalities in the practice of rheumatology, even on a global scale.