Biomedical big data is an important foundation for advancing precision medicine, disease prediction and early warning, and innovation in medical education. The integration of biomedical big data with artificial intelligence (AI) technologies represents a pivotal approach to construct a comprehensive and adaptive training system for medical students. By developing an AI-empowered integrated teaching platform that integrates five core modules, including structured medical record automatic generation, competency profiling, knowledge-based question answering, intelligent assessment, and decision-making, this study enrolled and trained 200 students who rotated in the Department of Neurology at the Second Affiliated Hospital of Anhui Medical University, while evaluating the platform's application efficacy. Results demonstrated that students in the observation group achieved significantly higher scores than those in the control group across dimensions such as perceived ease of use, perceived usefulness, and learning engagement. Additionally, the platform demonstrated ideal outcomes in terms of optimal path selection rate and average completion time in decision-making simulations, performance in knowledge-based interactive question answering, application accuracy, and response speed. This innovative teaching model enhanced students' comprehensive clinical competencies, refined their diagnostic and therapeutic reasoning, and strengthened their ability to conduct standardized diagnosis and treatment. Concurrently, students developed a deeper understanding of the breadth and depth of medicine, ultimately achieving desirable educational outcomes. Therefore, the AI-empowered, large-model collaborative teaching system based on biomedical big data provides a new paradigm for delivering precise and adaptive medical education.