AI technologies outperform or complement radiologist scoring in CT, MRI, and ultrasound imaging for rheumatology disorders, as shown in key EULAR 2025 studies.
Key Details
- 1AI-assisted HRCT outperformed expert radiologists in detecting progression of SSc-associated interstitial lung disease (ILD).
- 2A deep learning model integrating MRI findings achieved high accuracy for diagnosing axial spondyloarthritis and identified cases beyond standard criteria.
- 3Ultrasound AI models improved classification of giant cell arteritis lesions but showed limitations in smaller arteries.
- 4Machine learning approaches identified personalized cancer risk factors in systemic sclerosis using clinical and imaging data.
- 5Large language models show promise but mixed performance in osteoporosis risk stratification tasks based on imaging and clinical data.
Why It Matters
These EULAR 2025 findings validate the growing impact of AI in augmenting radiologic assessment and predictive analytics in rheumatology. Enhanced imaging AI can increase diagnostic accuracy, detect subtle disease changes, and underpin precision medicine strategies for complex rheumatic diseases.
Source
EurekAlert
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