Аннотация
The integration of artificial intelligence into biostatistics has become an important issue in medical education, offering new ways to improve the accuracy and objectivity of data analysis. This review provides an overview of current studies on the application of artificial intelligence in biostatistics and identifies effective approaches for training future healthcare professionals. The aim of this review is to assess the current state of artificial intelligence use in biostatistics for medical education and its potential to improve training quality, objectivity of analysis, and the development of professional skills. A systematic literature search was conducted in Embase, Web of Science, Google Scholar, and Ovid Medline up to December 2024. Studies focusing on artificial intelligence applications in biostatistics and medical education were analyzed. From 1.000 identified publications, only seven met the inclusion criteria. Two explored artificial intelligence in evaluating biostatistical data quality, while five examined its role in student learning outcomes. Artificial intelligence opens new perspectives for biostatistics in medicine. Deep learning models achieved sensitivity up to 95.4% in clinical case analysis and visualization. The creation of an international biostatistical database could support the broader integration of artificial intelligence into education and strengthen students’ understanding of statisticalmethods.Ключевыеслова:artificial intelligence, biostatistics, medical education, deep learning, data analysis, learning technologies.