Latent tuberculosis infection (LTBI) is a tuberculosis infection in which mycobacteria colonize the body without causing disease, but its early detection is important to control the spread of the infection.[1][3] The diagnosis of LTBI is indirect and is based on the detection of an immune response to mycobacterial antigens, which makes it difficult and complex.[1] The study analyzed articles from 2015 to 2025 from international databases (Medline, PubMed, Scopus) focused on the application of immunological tests and machine learning technologies in the detection of LTBI in high-risk groups.[1] Research has confirmed that a comprehensive approach in the diagnosis of LTBI - the simultaneous use of several immunological tests in combination with laboratory and instrumental methods - is justified.[1] The creation of a strategy for the detection of LTBI in individuals from risk groups can facilitate the detection of infection and play an important role in preventing the development of tuberculosis.[1] The possibility of using machine learning and artificial intelligence based on immunological tests will make it possible to determine the risk of developing active tuberculosis.[1]