An enhancing diagnostic pulmonary diseases diagnostic method for differentiating talaromycosis from tuberculosis.

ABSTRACT: Talaromycosis (TSM) affects immunocompromised individuals, particularly those with human immunodeficiency virus (HIV)/acquired immunodeficiency syndrome (AIDS), causing varied pulmonary abnormalities on chest computed tomography (CT). These features overlap with pulmonary tuberculosis, making accurate differentiation essential for appropriate treatment. This study utilized real patient data from the First Affiliated Hospital of Wenzhou Medical University. A machine learning model, termed bIPCACO-FKNN, was developed, integrating an ant colony optimization (ACO) algorithm with a fuzzy k-nearest neighbors (FKNNs) classifier. This model introduces an incremental proportional-integral-derivative control strategy to enhance the search efficiency of ACO. Comparative analysis with several algorith

SUBMITTER: Zhou Y 

PROVIDER: S-EPMC11872622 | biostudies-literature | 2025 Feb

REPOSITORIES: biostudies-literature