The potential and prospect of GPT-enabled pulmonary function testing

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 decision-making. 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.

Key Words: generative pre-trained transformer; artificial intelligence; chronic obstructive pulmonary diseases; asthma