AIMC Topic: Spondylarthritis

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Machine learning-based prediction of radiographic progression in patients with axial spondyloarthritis.

Clinical rheumatology
INTRODUCTION: Machine learning is applied to characterize the risk and predict outcomes in multi-dimensional data. The prediction of radiographic progression in axial spondyloarthritis (axSpA) remains limited. Hence, we tested the feasibility of supe...

Deep learning algorithms for magnetic resonance imaging of inflammatory sacroiliitis in axial spondyloarthritis.

Rheumatology (Oxford, England)
OBJECTIVE: The aim of this study was to develop a deep learning algorithm for detection of active inflammatory sacroiliitis in short tau inversion recovery (STIR) sequence MRI.

Incorporating natural language processing to improve classification of axial spondyloarthritis using electronic health records.

Rheumatology (Oxford, England)
OBJECTIVES: To develop classification algorithms that accurately identify axial SpA (axSpA) patients in electronic health records, and compare the performance of algorithms incorporating free-text data against approaches using only International Clas...

Detection of Flares by Decrease in Physical Activity, Collected Using Wearable Activity Trackers in Rheumatoid Arthritis or Axial Spondyloarthritis: An Application of Machine Learning Analyses in Rheumatology.

Arthritis care & research
OBJECTIVE: Flares in rheumatoid arthritis (RA) and axial spondyloarthritis (SpA) may influence physical activity. The aim of this study was to assess longitudinally the association between patient-reported flares and activity-tracker-provided steps p...

Application of machine learning in the diagnosis of axial spondyloarthritis.

Current opinion in rheumatology
PURPOSE OF REVIEW: In this review article, we describe the development and application of machine-learning models in the field of rheumatology to improve the detection and diagnosis rates of underdiagnosed rheumatologic conditions, such as ankylosing...