The use of large language model in patient education

Patient education is a crucial aspect of healthcare, but traditional methods often fail to account for individual differences in literacy and comprehension. Recent advances in natural language processing offer a solution. This presentation will discuss the application of large language models to generate personalized patient education materials tailored to specific patient needs and literacy levels. Our research demonstrates significant improvements in patient understanding, engagement, and health outcomes. Additionally, we explore the potential for these models to address health disparities by providing culturally sensitive and multilingual resources. This innovative approach has far-reaching implications for patient empowerment, health literacy, and healthcare outcomes. Join us to explore the cutting-edge intersection of AI and patient education.