Background: Physiology is a foundational discipline in medical education, providing the scientific basis for understanding human body functions and clinical decision-making. Traditional teaching approaches, although effective, often face limitations related to large student groups, variability in learning pace, and limited opportunities for interactive, data-driven learning. Objective: This study aims to identify and describe effective methods for incorporating artificial intelligence (AI) into the teaching of physiology in higher medical education institutions.Methods: A structured narrative analysis was conducted to examine AI-assisted educational technologies, focusing on simulation-based learning, adaptive e-learning systems, intelligent tutoring platforms, and data-driven assessment tools relevant to physiology instruction.Results: Five categories of effective AI-supported strategies were identified: AI-enabled physiological simulations, intelligent tutoring systems, adaptive learning platforms, predictive learning analytics, and AI-driven virtual laboratory environments. These approaches enhance conceptual understanding, personalise the learning experience, and support competency-based education.
Conclusion: AI provides valuable tools to improve the teaching and learning of physiology. When integrated responsibly, AI enhances interactivity, strengthens analytical thinking, and supports deeper comprehension of physiological principles essential for future medical professionals.

Artificial Intelligence; Physiology Education; Medical Education; Intelligent Tutoring Systems; Adaptive Learning; Virtual Laboratories; Simulation-Based Learning; Machine Learning; Educational Technology; Digital Pedagogy; Learning Analytics.

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