Identification of Gene Expression Biomarkers Predictive of Latent Tuberculosis Infection Using Machine Learning Approaches

Abstract excerpt

Latent tuberculosis infection (LTBi) affects nearly a quarter of the global population, yet current diagnostic methods are limited by low sensitivity and specificity. This study applied an integrative bioinformatics framework, incorporating machine learning techniques, to identify robust gene expression biomarkers associated with LTBi. We analyzed four publicly available transcriptomic datasets from peripheral...

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