肺功能检查是评估呼吸系统健康及管理慢性阻塞性肺病（chronic obstructive pulmonary disease，COPD）、哮喘等 疾病的关键工具。生成式预训练转换器（generative pre-trained transformer，GPT）凭借其强大的自然语言处理与大数据分析能 力，可高效整合多维度患者信息，生成精准诊断报告和治疗建议，显著提升解读效率并辅助临床决策。其应用涵盖监测预警、综合分析、诊断评估及个性化治疗方案制定，尤其在COPD、哮喘等慢性气道疾病管理中，通过实时追踪肺功能数据、症状及用药反应提供个体化建议；在肺间质疾病中辅助动态评估与预后预测；在外科领域支持手术耐受性判断与围术期管理优化。此外，GPT可预测药物耐受性，提供用药调整意见，并结合生活方式与环境因素进行综合健康干预。该技术还拓展了远程医疗服务，缓解资源分布不均问题，通过数据整合转换、智能分析报告及远程咨询提升服务可及性。实施中需应对隐私保护、内容准 确性、数据预处理、用户体验及系统稳定性等挑战，可通过加密技术、构建医疗知识库、开发数据转换模块、优化界面设计等措施保障应用安全可靠。

Pulmonary function testing (PFT) is a critical tool for assessing respiratory health and managing diseases such as  chronic obstructive pulmonary disease (COPD) and asthma. Leveraging its powerful natural language processing and big data analytics  capabilities, Generative pre-trained transformer (GPT) can efficiently integrate multidimensional patient data to generate precise  diagnostic reports and treatment recommendations, significantly enhancing interpretation efficiency and supporting clinical decisionmaking. Its applications encompass monitoring and early warning, comprehensive analysis, diagnostic assessment, and personalized  treatment plan formulation. Particularly in managing chronic airway diseases like COPD and asthma, GPT provides individualized  advice by tracking pulmonary function data, symptoms, and medication responses in real-time; it assists in dynamic assessment and  prognosis prediction for interstitial lung diseases; and in the surgical domain, it supports the evaluation of operative tolerance and  optimization of perioperative management. Furthermore, GPT can predict drug tolerance issues, offer suggestions for medication  adjustments, and provide comprehensive health interventions incorporating lifestyle and environmental factors. This technology also  extends remote medical services, mitigating disparities in healthcare resource distribution by enhancing service accessibility through  data integration and conversion, intelligent analysis and reporting, and remote consultations. Implementation requires addressing  challenges such as privacy protection, content accuracy, data preprocessing, user experience, and system stability. These can be  addressed through measures like encryption technologies, constructing medical knowledge bases, developing data conversion modules, and optimizing interface design to ensure the secure and reliable application of GPT in pulmonary function testing.