Exploration of the Application Mode of Artificial Intelligence Assisted Evidence Based Medicine Collaborative Teaching

Abstract

Modern generative artificial intelligence technologies are fundamentally reshaping the pedagogical paradigm of evidence-based medicine (EBM). This article systematically articulates the mechanisms by which AI augments EBM instruction—encompassing large language models, knowledge graphs, and rule engines—with a specific focus on the "reasoning visualization" pedagogical approach introduced by emerging medical evidence-based AI agents such as DeepRare. In contrast to the functional orientation of general-purpose large language models, DeepRare operationalizes a complete "hypothesis-verification-reflection" reasoning loop, thereby transforming the implicit clinical reasoning processes of conventional instruction into observable, replicable, and critically assessable educational content. Building upon this foundation, the article dissects the concrete pathways of AI integration in EBM teaching across four interdependent dimensions: evidence acquisition and screening, evidence appraisal and the cultivation of critical thinking, evidence synthesis and clinical translation, and teaching evaluation with feedback mechanisms. The inquiry further explores the reconceptualization of teaching models, encompassing competency-adaptive personalized learning trajectories, human-computer collaborative decision-making exercises that promote shared clinical reasoning between learners and intelligent systems, and the "Internet plus evidence-based teaching" paradigm that extends educational impact beyond traditional classroom settings. In confronting practical challenges—including technological dependability, the paucity of empirical validation regarding educational outcomes, ethical and equity considerations, and the digital competency gaps among both instructors and learners—this article advances an integrated four-pronged future agenda comprising technological refinement, curricular redesign, faculty professional development, and deepened empirical research. The ultimate objective is to furnish an operational foundation for the intelligent transformation of EBM education that is congruent with the evolving demands of medical development and talent cultivation in China.