A comparative study plan on the clinical application effects of large language models and specialized GPTs in OSA consultation and management

This research plan aims to compare the clinical application effects of large language models (such as DeepSeekGPT) and specialized disease GPT (such as BAIMGPT) in the consultation and management of obstructive sleep apnea (OSA). A multicenter real-world research design is adopted, involving 1000 OSA patients or high-risk individuals. Through user cross-sectional evaluations and third-party expert reviews, the performance of the two models in aspects such as convenience, friendliness, security, accuracy of problem understanding, accuracy of answers, voice interaction, visual empowerment, and the degree of patient needs is assessed. The research focuses on the roles of the two models in OSA screening, diagnostic accuracy, and personalized prevention and treatment, and explores their potential in enhancing patient education, doctor training, and coverage of primary medical care. The research results will provide empirical evidence for the optimized application of artificial intelligence technology in OSA diagnosis and treatment, and promote the development of precision medicine and health management.

Key Words: obstructive sleep apnea; BAIMGPT; DeepSeek GPT