Routine biomarker profile for the prediction of clinical phenotypes of adult-onset Still's disease using unsupervised clustering algorithm.

The study demonstrates the potential of integrating traditional biomarkers with unsupervised clustering algorithms in understanding the heterogeneity of AoSD. These findings suggest new avenues for developing personalized treatment strategies, though further validation in larger, prospective studies is necessary.