[Current Status of Multidisciplinary Team Consultation for Lung Cancer and Prospects under the Empowerment of Medical Large Models].

内容摘要

Lung cancer ranks among malignant neoplasms with the highest incidence and mortality, and its diagnosis and treatment are complicated, requiring multidisciplinary participation. Multidisciplinary team (MDT) consultation is the core model for modern lung cancer management. By pooling the expertise of specialists from diverse disciplines, MDT develops optimal individualized treatment regimens for patients and markedly improves diagnostic and therapeutic quality as well as patient prognosis. This article systematically summarizes the organizational framework, standardized procedures and clinical value of lung cancer MDT, alongside key problems in its popularization including obstacles in data integration, inconsistent decision-making efficiency and imbalanced resource allocation. It elaborates on the innovative effect of new technologies represented by artificial intelligence large language models on conventional MDT modes, and analyzes their application value in high-efficiency integration of multimodal medical data, real-time evidence-based decision-making support, optimization of consultation procedures and resources, as well as precise individualized treatment, so as to furnish theoretical basis and development ideas for establishing a new-generation intelligent, efficient and precise lung cancer MDT platform.
. 【中文题目：肺肿瘤多学科会诊现况
与医用大模型赋能下展望】 【中文摘要：肺肿瘤为发病率与死亡率最高的恶性肿瘤之一，诊疗复杂，涉及多学科。多学科诊疗（multidisciplinary team, MDT）是现代肺肿瘤诊疗核心模式，通过整合多学科专家智慧，为患者制定个体化最优方案，可显著提升诊疗质量和预后。本文系统梳理了肺肿瘤MDT的组织架构、标准流程、临床价值以及推广中存在的数据整合困难、决策效率不一、资源分配不均等关键问题；重点探讨以人工智能大语言模型为代表的新技术对传统MDT模式的革新作用，分析其在多模态医疗数据的高效融合、实时循证的决策支持、会诊流程与资源优化、精准个体化治疗等方面的应用价值，为构建新一代智能、高效、精准的肺肿瘤MDT平台提供理论依据与发展思路。
】 【中文关键词：肺肿瘤；多学科诊疗；诊疗模式；大语言模型；临床决策支持】.