AI+ empowering respiratory medicine education： building a digital health competence training system oriented towards new quality productivity

Driven by the converging forces of metaverse medicine and the new quality productive forces in healthcare, respiratory medicine education must evolve from the traditional model of ‘knowledge delivery and guideline recitation’ toward a forward-looking ‘AI+ Respiratory New-Quality Productive Center’- a pioneering hub that integrates pedagogical prototyping with the incubation of interdisciplinary talent. Contemporary respiratory physicians, beyond mastering core clinical competencies, must also cultivate digital health literacy: the ability to critically understand, evaluate, and appropriately apply emerging technologies such as artificial intelligence (AI), the Internet of Things (IoT), digital twins, and extended reality (XR). Within human - AI collaborative multidisciplinary teams (MDTs) and frameworks augmented by ‘digital expert avatars,’ they should be empowered to make safe clinical decisions, conduct risk stratification, and simulate therapeutic strategies. International evidence-based medical education research indicates that AI has already been piloted in areas such as radiological interpretation, clinical skills assessment, adaptive learning, and real-time feedback. However, these efforts largely remain fragmented ‘point innovations’, lacking an integrated curriculum that embeds cross-disciplinary integration, structured design, and proactive governance. Respiratory medicine - by virtue of its inherently multimodal nature and richly visualizable longitudinal data (including imaging, pulmonary function tests, blood gas analysis, dynamic symptom trajectories, wearable-derived metrics, ventilator parameters, and sleep monitoring data) - is uniquely positioned to leverage digital twin and immersive XR scenarios to systematically address the core limitations of conventional classrooms: phenomena that are ‘invisible, difficult to simulate, and hard to reason through.’ This proposal is grounded in international consensus on digital health and AI competencies, systematically aligning with authoritative frameworks such as the Digital Education Competency Outcomes for Doctors in Europe (DECODE) and the Best Evidence Medical Education (BEME) Collaboration. It establishes a four-dimensional instructional framework encompassing Knowledge - Tools - Clinical Reasoning - Ethical Governance. At its core is an ‘AI + Case Chain’ modular curriculum: Pre-class: diagnostic pre-assessments and learner profiling to identify cognitive baselines; In-class: multimodal data visualization integrated with conversational standardized patients or interactive intelligent cases to enable immersive, context-rich clinical reasoning training; Post-class: learning analytics-driven personalized feedback loops that feed back into scholarly inquiry, creating a seamless teaching - learning- research cycle. Assessment and safeguard mechanisms center on a multi-modal evaluation system based on Objective Structured Clinical Examinations (OSCEs), adhering strictly to the principle of ‘AI-supported, never AI-substituted’ assessment. Ethical compliance and trustworthy AI governance -including data privacy protection, algorithmic bias mitigation, clear delineation of human -AI responsibility boundaries, and academic integrity - are embedded as non-negotiable safeguards. Ultimately, by leveraging interdisciplinary innovation centers and reusable digital infrastructures, this initiative transforms the traditional classroom into a next-generation smart learning environment characterized by visualizability, deep interactivity, and reasoning-driven pedagogy, systematically cultivating a vanguard cohort of talent ready to lead ‘smart respiratory care centers’ and ‘metaverse medicine’ practices by 2035.

Key Words: metaverse medicine; digital health competency; digital expert avatars; digital twin lung; multimodal learning and visualized reasoning; trustworthy AI governance and ethics