Enhancing predictions of subclinical cardiac dysfunction in SLE patients through integrative machine learning analysis.

From an overall trend perspective, in most age categories, the results of GLPS, GLPS-A2C, GLPS-A4C and GLPS-APLAX in the SLE group are notably different from those in the healthy control group, with corresponding values significantly greater than −20%.

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