Prospects for the use of artificial intelligence to predict the spread of tuberculosis infection in the WHO European Region

Objective — to analyze the prospects of using artificial intelligence and neural networks create a geospa­tial model TB transmission forecast its spread in WHO European Region available analytical databases.
 Materials methods. The research was carried out for period October 2022 March 2023. Digital access following full-text abstract databases used as main source research: EBSCO Information Base Package, world’s largest single scientific metric platform Scopus, freely accessible search system Google Scholar, MEDLINE with Full Text, Dyna Med Plus, eBooks Clinical Collection, database publications Thomson Reuters Web Science Core Collection WoS, statistical data from Ministry Health Ukraine Public Center, SCIE, SSCI, online National Scientific Medical Library Ukraine, AHCI.
 Results discussion. Migration processes Europe still remain global trend difficulties countries that receive migrants. Adverse living conditions, close contact, poor nutrition, mental physical stress are what refugees migrants face. combination these risk factors insufficient health services increases vulnerability infection. In addition, delay diagnosis leads treatment outcomes continued infection other people.The optimal way predict cities, where significant number arrived, is mathematical technology intelligence. By analyzing large amount data, can quickly efficiently identify connections between various future development epidemic. For example, on incidence different regions world, well patients diseases affect human immune system, make about epidemic future.
 Conclusions. Today, creation simulator program geospatial functioning city interaction people during day relevant. Understanding natural history among recently arrived important we consider how best implement control such populations.