28 July 2025
Artificial intelligence (AI) is no longer a future concept, it's already in clinic. From diagnosis to disease monitoring, it's reshaping the rheumatology practice today.
A new special issue of Rheumatology Advances in Practice explores how AI is being applied today, and what it means for the future of our specialty. Here are seven key developments highlighted in the issue.
1. The future is here
As Vincenzo Venerito writes in the issue’s editorial, we are living in a moment where the future we once imagined is already here. The digital tools and algorithms that once seemed speculative are now part of clinical routines, shaping how we assess, diagnose and treat patients.
2. Remote assessment is becoming more advanced
The MeFisto system represents a breakthrough in remote patient care. Using advanced hand motion recognition, it can assess disease activity in patients with rheumatoid arthritis without the need for in-person appointments. This is a major step forward for accessibility, particularly for those with limited mobility or remote living situations.
3. Large language models are changing how we access knowledge
The emergence of large language models (LLMs) has introduced powerful new tools for clinical informatics. These models can synthesise complex medical knowledge, support decision-making and improving access to evidence in time-pressured clinical settings.
4. AI is improving diagnostic imaging
Artificial intelligence is advancing imaging through techniques such as radiomics and convolutional neural networks (CNNs). These technologies are already achieving diagnostic accuracy comparable to experienced clinicians in detecting radiographic changes, especially in complex or subtle cases.
5. Unsupervised learning is revealing hidden patient groups
By applying AI algorithms to large datasets, researchers are uncovering new patient subgroups that were previously undetectable. These unsupervised learning techniques are helping to redefine disease categories and guide more personalised treatment strategies.
6. Ethical considerations are front and centre
With these advances come important ethical questions. Issues of data privacy, algorithmic bias and fair access to AI tools must be addressed. The rheumatology community has a responsibility to ensure that AI enhances equity in care rather than reinforcing existing disparities.
7. Medical education must adapt
AI is now part of rheumatology, and that means our training must evolve. Future clinicians need to understand how AI works, how to use it safely and how to critically evaluate its outputs. It is no longer just about adopting new technology, but about shaping it responsibly.