Abstract. Premature ageing is one of the most pressing problems of modern medicine. It is associated with accelerated wear and tear of tissues and organs, which can lead to the development of chronic diseases and reduced life expectancy. In recent years, artificial intelligence (AI) has started to play a key role in healthcare, providing new tools for diagnosis and prognosis. This article reviews current AI advances in the study of premature aging processes, including the use of machine learning to analyse aging biomarkers, estimate biological age, and predict the risk of age-related diseases.

Key words: artificial intelligence, premature ageing, biological age, machine learning, biomarkers.