Artificial intelligence in medical education: enhancing the acquisition of foundational disciplines through the case of the “Human anatomy” course

Abstract

Background. In the era of global digitalization of the educational environment, higher education—particularly medical education—is undergoing an active integration of innovative technologies. The rapid advancement of medical science, the growing volume of educational content, and the imperative to cultivate practice-oriented competencies underscore the limitations of traditional teaching approaches, which often fail to adequately address the educational needs of a new generation of learners. The application of artificial intelligence (AI) technologies in the learning process offers broad opportunities for personalizing educational trajectories, facilitating interactive acquisition of complex theoretical knowledge, and fostering the development of clinical reasoning. These approaches are of particular significance in the teaching of human anatomy, a foundational discipline that provides the basis for the subsequent clinical training of future physicians. Objective. To examine the potential of applying AI-based methods to optimize the teaching of core medical disciplines, thereby enhancing learning efficiency and improving the overall quality of physician training. Results. This article explores the potential of artificial intelligence (AI) applications in advancing the educational process within higher medical education, with a focus on fundamental disciplines. The findings suggest that the integration of intelligent technologies enables the personalization of learning trajectories, increases the effectiveness of knowledge acquisition, and strengthens students’ motivation to learn. Emphasis is placed on the role of AI in the development of modern educational resources, automated generation of assessment tools, clinical vignettes, and interactive learning materials, thereby expanding the pedagogical toolkit of instructors and enhancing the quality of medical training. Conclusions. The incorporation of AI-driven methodologies into the study of fundamental medical disciplines holds considerable promise for improving the quality of education in medical schools. For students, AI supports individualized learning, facilitates more effective assimilation of theoretical content, promotes the development of clinical reasoning skills, and enhances intrinsic motivation for academic engagement. For educators, AI technologies provide opportunities to optimize the design of teaching resources, refine assessment systems, and implement interactive, practice-oriented teaching strategies. The synergy between pedagogical expertise and the innovative potential of AI contributes to more effective physician training and the development of high-level professional competence.