Machine learning classifiers on patient-reported data and urine biomarkers reach moderate AUC (up to 0.72) for PCR-confirmed Chlamydia in 93 samples, with combined features yielding slightly higher peak performance and lower variability.
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Machine Learning-Based Pre-Test Risk Stratification for PCR-Confirmed Chlamydia Using Patient-Reported Data and Urine Biomarkers
Machine learning classifiers on patient-reported data and urine biomarkers reach moderate AUC (up to 0.72) for PCR-confirmed Chlamydia in 93 samples, with combined features yielding slightly higher peak performance and lower variability.