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Adaptive user interface framework powered by a large language model for culturally sensitive virtual healthcare applications

Authors: Ghosh, Akash; Yan, Yan; Lin, Wenjun;

Adaptive user interface framework powered by a large language model for culturally sensitive virtual healthcare applications

Abstract

In this research, we propose the development of anAdaptive User Interface (UI) Framework for virtual healthcareapplications, powered by a Large Language Model (LLM). Theintention is to revolutionize the way healthcare services arerendered by creating a real-time responsive system that catersto diverse patient needs. Unlike conventional healthcareapplications, this framework utilizes various sensors andinteractive inputs to continuously adapt to users' feedback. Itharnesses the potential of deep learning to process this feedbackand make culturally sensitive adaptations, ensuring morepersonalized and effective care for Indigenous, Black, andPeople of Colour (IBPOC) populations. A unique aspect of thissystem is that its adaptations are not predetermined; instead, itdynamically generates changes based on the user feedbackanalyzed by the LLM. To demonstrate the efficacy of thisframework, a demo healthcare application is being developed.We expect this initiative to significantly contribute to the field ofvirtual healthcare by introducing a more inclusive, personalized,and adaptive platform, ultimately leading to improved patientcare outcomes.

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