Abstract:

The rapid evolution of modern lifestyles has led to increasing public demand for proactive health interventions and the effective management of major chronic diseases. Traditional health management approaches have demonstrated limitations in addressing diverse and complex health needs， whereas digital therapeutics powered by multimodal large language models present transformative opportunities for advancing intervention strategies in chronic disease care. By integrating big data， artificial intelligence， and other cutting-edge information technologies， digital therapeutics deliver personalized， remote， and data-driven solutions that enhance the prevention， monitoring， and management of major chronic conditions. These innovations not only improve clinical outcomes but also optimize the allocation of healthcare resources and elevate patients′ quality of life. Multimodal large language models， acting as "digital health assistants，" enable intelligent integration of text and visual data to support medical image interpretation， real-time health monitoring， and conversational clinical decision-making for both clinicians and patients. This paper aims to investigate the integration of multimodal large language models into digital therapeutics for proactive health management， examining their applications， current domestic and international research advancements， existing challenges， and future development trends， thereby offering theoretical insights and practical guidance for the advancement of proactive healthcare systems.

Key words: multimodal large language model, proactive health management, digital therapeutics