Ключевое слово: «machine learning»

This article speaks about the use of artificial intelligence (AI) in tuberculosis (TB) screening in the Republic of Sakha (Yakutia), focusing on improving diagnostic accuracy and optimizing medical data analysis. The study highlights the potential of machine learning to enhance the quality of TB diagnosis and reduce the time needed for analyzing radiological images. Key areas of improvement include faster image analysis, autonomous patient routing, and integration of AI systems with healthcare information systems. Pilot studies were conducted at institutions such as the E.N. Andreev Phthisiopulmonology Center and M.V. Lomonosov Moscow State University, showcasing the effectiveness of AI algorithms in analyzing X-ray images. The results demonstrate significant advancements in diagnostic accuracy and efficiency, underscoring the value of AI in TB screening.