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Enhancing Healthcare User Interfaces Through Large Language Models Within the Adaptive User Interface Framework

  • Akash Ghosh,
  • Bo Huang,
  • Yan Yan,
  • Wenjun Lin

摘要

In the pursuit of enhancing digital user experiences within healthcare, this research investigates the novel application of Large Language Models (LLMs) in the Adaptive User Interface Framework (AUIF). This framework aims to redefine user interaction by providing real-time, personalized interface adjustments. By systematically applying LLMs to user interface enhancement, the AUIF addresses the static nature of current digital health platforms, offering a dynamic and adaptive alternative that responds to individual user behaviors and preferences. This study explores the pioneering integration of LLMs for user experience (UX) improvement recommendations and real-time HyperText Markup Language (HTML) content adjustments, marking a significant step forward in intelligent user interface design. The implications of this research are vast, with the potential to improve patient engagement, and satisfaction, and to address the pressing need for interfaces that adapt to diverse user behaviors and preferences.