Abstract: In the era of precision medicine, therapeutic strategies for epidermal growth factor receptor (EGFR) mutation-positive non-small cell lung cancer (NSCLC) have become increasingly advanced. However, conventional multidisciplinary team (MDT) models fail to address the demands of dynamic whole-course disease management. This review proposes an evolved learning-oriented MDT system for the standardized management of EGFR mutation-positive NSCLC. Grounded in evidence-based medicine, centered on expert decision-making, and supported by digital integration, this system enables the comprehensive evaluation of patients' individual characteristics, including performance status, psychosocial conditions, and economic affordability. This article elucidates the core management objectives and key PICO-style clinical questions for EGFR mutation-positive NSCLC across critical disease stages, including resectable early-stage disease, stage Ⅲ disease, metastatic/oligoprogressive disease, and tyrosine kinase inhibitor-resistant disease. Based on updated quantitative clinical evidence, we develop a structured framework for the learning-oriented MDT system, covering a multidimensional collaborative structure, standardized node-based workflows, a full-cycle information integration platform, quantitative evaluation indicators, and a closed-loop optimization mechanism. Notably, we propose a multicenter prospective randomized controlled trial design to validate the clinical efficacy of this system. This review analyzes the implementation limitations and potential social impacts of the system and proposes phased optimization and mitigation strategies. This work provides a theoretical framework and practical guidance for establishing a standardized, precise, and humanistic whole-course management model for EGFR mutation-positive NSCLC.