Abstract
The emergence of generative artificial intelligence and Large Language Models (LLMs)
has brought revolutionary applications in the medical field, especially in the field
of smart inhalers, where LLMs show great potential. LLMs can optimize the functionality
of smart inhalers, enhance patient education and feedback mechanisms, and support
personalized medical decision-making through natural language processing and deep
data analysis. However, the application of these technologies also presents numerous
challenges. This paper systematically reviews the prospective applications of LLMs
in smart inhalers, discusses the advantages of LLMs in improving patient experience,
optimizing medical processes, and facilitating data-driven decision-making, and analyzes
the current technical barriers and obstacles. The article envisions the future development
of LLMs in smart inhalers, advocating for multidisciplinary collaboration to fully
harness their potential while effectively addressing associated risks, thereby advancing
medical services toward greater intelligence, personalization, and efficiency.
Keywords
large language models - smart inhalers - patient education - data privacy - medical
decision-making
