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https://dx.doi.org/10.48550/ar...
Article . 2023
License: CC BY
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MemoryCompanion: A Smart Healthcare Solution to Empower Efficient Alzheimer's Care Via Unleashing Generative AI

Authors: Zheng, Lifei; Heo, Yeonie; Fang, Yi;

MemoryCompanion: A Smart Healthcare Solution to Empower Efficient Alzheimer's Care Via Unleashing Generative AI

Abstract

With the rise of Large Language Models (LLMs), notably characterized by GPT frameworks, there emerges a catalyst for novel healthcare applications. Earlier iterations of chatbot caregivers, though existent, have yet to achieve a dimension of human-like authenticity. This paper unveils `MemoryCompanion' a pioneering digital health solution explicitly tailored for Alzheimer's disease (AD) patients and their caregivers. Drawing upon the nuances of GPT technology and prompt engineering, MemoryCompanion manifests a personalized caregiving paradigm, fostering interactions via voice-cloning and talking-face mechanisms that resonate with the familiarity of known companions. Using advanced prompt-engineering, the system intricately adapts to each patient's distinct profile, curating its content and communication style accordingly. This approach strives to counteract prevalent issues of social isolation and loneliness frequently observed in AD demographics. Our methodology, grounded in its innovative design, addresses both the caregiving and technological challenges intrinsic to this domain.

Keywords

FOS: Computer and information sciences, Computer Science - Machine Learning, Computer Science - Computation and Language, Artificial Intelligence (cs.AI), Computer Science - Artificial Intelligence, Computer Science - Human-Computer Interaction, Computation and Language (cs.CL), Human-Computer Interaction (cs.HC), Machine Learning (cs.LG)

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
0
Average
Average
Average
Green