CCL4 and neurosyphilis: Feature selections were further analysed for the using different machine learning model for the diagnosis and progression predicting of neurosyphilis.<h4>Results</h4>Machine learning-based feature selection identified a three-cytokine panel (RANTES, MIP-1β, and IL-3) that effectively distinguished syphilis patients from controls (AUC = 0.869, 95% CI: 0.821-0.917).