Application and Development of Large Language Models in Smart Inhalers - Guo, Wenxu; Cheng, Zhihong; Wang, Jian (Pharmaceutical Fronts, 2025)
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