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This study aims to further improve and expand the WB-MRI imaging evaluation cohort of axSpA patients to complete dynamic follow-up and condition assessment. Based on the WB-MRI features, the association of WB-MRI signs with disease activity, inflammation, and structural damage will be analyzed. At the same time, in-depth data mining was conducted and machine learning was used to construct a new axSpA disease activity assessment model based on WB-MRI data, and the accuracy and reliability of the model were clearly evaluated in the discovery cohort and validation cohort.
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