This article examines the application of artificial intelligence technologies for training and objectively assessing basic laparoscopic skills using the BÉSTA 2.0 simulation platform. The paper presents the system architecture, computer vision algorithms, stages of neural network training, and performance results. A three-phase study demonstrated high assessment accuracy (up to 95% agreement with expert ratings) and strong reproducibility of outcomes. Key limitations and mitigation strategies are discussed. Automated evaluation of the endosurgical skills enables scalable, instructor-independent feedback, improves training efficiency, and ensures real-time insight into trainee performance. The findings emphasize the potential of incorporating AI into laparoscopic training and, more broadly, into contemporary surgical education.

The work is devoted to the role of simulation education using manikins and their effectiveness in pediatrics. Five basic skills were selected, and the level of knowledge and skills of students “BEFORE” and “AFTER” completing the pediatrics course in the simulation center was also assessed. Answering the questions specified in the questionnaire, students assessed themselves as 0, 1, 2 points. As a result of the analysis, it was found that students’ mastery of skills is less developed than their theoretical knowledge, and after the course, their theoretical knowledge and, most importantly, practical skills improved. There is a statistically significant difference between the average arithmetic assessment “BEFORE” and “AFTER” completing the course.

Medical care in case of emergency occurs under conditions of limited effort and time, accompanied by physical and psycho-emotional stress. The presence of an obstetric patient in an emergency area doubles the burden on medical staff. The article discusses the experience of developing a scenario and conducting large-scale interprofessional simulation training on emergency medical care and management of sudden childbirth in emergency situations for students under an individual professional retraining plan in the specialty “General Medicine”. The results obtained will make it possible to adjust educational activities.

This article presents the results of the initial stage of a study aimed at assessing the awareness and readiness of senior medical students to master the FAST protocol (Focused Assessment with Sonography for Trauma) in pediatrics. Based on a survey of 127 students (Russian-speaking and English-speaking groups), key challenges in modern medical education were identified: insufficient practical training, limited access to simulation technologies, and significant cross-cultural differences in the perception of innovative teaching methods. The study found that 86% of students consider simulation training essential, yet only 12% of Russian universities are equipped with modern tools. English-speaking students demonstrated twice the readiness for hands-on learning, linked to their access to international educational resources. The results underscore the need to integrate video-based learning, VR technologies, and clinical case studies into curricula. The article proposes concrete steps for modernizing medical education, including the creation of a national platform with open-access courses and the implementation of mandatory simulation modules.

Lioce L. (Ed.), Lopreiato J. (Founding Ed.), Anderson M., Deutsch, E.S., Downing D., Robertson J.M., Diaz D.A., and Spain A.E. (Assoc. Eds.), and the Terminology and Concepts Working Group (2024), Healthcare Simulation Dictionary–Third Edition. Rockville, MD: Agency for Healthcare Research and Quality; January 2025. AHRQ Publication No. 24-0077. DOI: https://www.ahrq.gov/ patient-safety/resources/simulation/terms.html.