Søren Andreas Just, MD, PhD: Developing AI to Mitigate Rheumatologist Shortages for Disease Assessment

Artificial intelligence (AI) joint assessment performed similarly to that of specialized rheumatologists and was able to accurately assess disease activity in joints, according to findings from 2 new studies.

Data from the studies were presented by Søren Andrea Just, MD, PhD, associate professor, University of Southern Denmark, and Odense University Hospital - Svendborg, at the American College of Rheumatology (ACR) Convergence 2024, held November 14-19 in Washington, DC.

“We are getting fewer and fewer rheumatologists across both here in the US, but also across Europe and other countries, and there's more and more patients, so we have to try to think differently. And then we thought, maybe AI robotics could be at least part of the solution, because if they could give high quality assessment of disease activity, especially in places where there are fewer, maybe no rheumatologists, [this] could really elevate the level of care for patients without the need for more persons,” Just told HCPLive® during the meeting.

During our conversation, Just discussed both studies that he is presenting at the meeting and how the AI performance matched clinician assessment of disease.

“I really hope, that these automated systems could help with a very fast assessment… to take some of the pressure off the rheumatologist and at the same time giving a good quality assessment for the patient,” Just said.

REFERENCES

1. Frederiksen BA, Danielsen MA, Hamer HB, et al. Automated Ultrasound System ARTHUR with AI Analysis DIANA Matches Expert Rheumatologist in Hand Joint Assessment of Rheumatoid Arthritis Patients. Presented at: ACR Convergence 2024; November 14-19; Washington, DC. Abstract L20

2. Weber A, Danielsen MA, Fredericksen BA, et al. Performance of an Artificial Intelligence Model Compared to Multiple Human Experts in Scoring Synovitis Severity and Osteophyte Severity on Joint Ultrasound Images. Presented at: ACR Convergence 2024; November 14-19; Washington, DC. Abstract L04