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用于痴呆症护理和研究的大语言模型介绍

Introduction to Large Language Models (LLMs) for dementia care and research.

作者信息

Treder Matthias S, Lee Sojin, Tsvetanov Kamen A

机构信息

School of Computer Science & Informatics, Cardiff University, Cardiff, United Kingdom.

Olive AI Limited, London, United Kingdom.

出版信息

Front Dement. 2024 May 14;3:1385303. doi: 10.3389/frdem.2024.1385303. eCollection 2024.

Abstract

INTRODUCTION

Dementia is a progressive neurodegenerative disorder that affects cognitive abilities including memory, reasoning, and communication skills, leading to gradual decline in daily activities and social engagement. In light of the recent advent of Large Language Models (LLMs) such as ChatGPT, this paper aims to thoroughly analyse their potential applications and usefulness in dementia care and research.

METHOD

To this end, we offer an introduction into LLMs, outlining the key features, capabilities, limitations, potential risks, and practical considerations for deployment as easy-to-use software (e.g., smartphone apps). We then explore various domains related to dementia, identifying opportunities for LLMs to enhance understanding, diagnostics, and treatment, with a broader emphasis on improving patient care. For each domain, the specific contributions of LLMs are examined, such as their ability to engage users in meaningful conversations, deliver personalized support, and offer cognitive enrichment. Potential benefits encompass improved social interaction, enhanced cognitive functioning, increased emotional well-being, and reduced caregiver burden. The deployment of LLMs in caregiving frameworks also raises a number of concerns and considerations. These include privacy and safety concerns, the need for empirical validation, user-centered design, adaptation to the user's unique needs, and the integration of multimodal inputs to create more immersive and personalized experiences. Additionally, ethical guidelines and privacy protocols must be established to ensure responsible and ethical deployment of LLMs.

RESULTS

We report the results on a questionnaire filled in by people with dementia (PwD) and their supporters wherein we surveyed the usefulness of different application scenarios of LLMs as well as the features that LLM-powered apps should have. Both PwD and supporters were largely positive regarding the prospect of LLMs in care, although concerns were raised regarding bias, data privacy and transparency.

DISCUSSION

Overall, this review corroborates the promising utilization of LLMs to positively impact dementia care by boosting cognitive abilities, enriching social interaction, and supporting caregivers. The findings underscore the importance of further research and development in this field to fully harness the benefits of LLMs and maximize their potential for improving the lives of individuals living with dementia.

摘要

引言

痴呆症是一种进行性神经退行性疾病,会影响认知能力,包括记忆、推理和沟通技巧,导致日常活动和社交参与逐渐下降。鉴于最近诸如ChatGPT之类的大语言模型(LLMs)的出现,本文旨在全面分析它们在痴呆症护理和研究中的潜在应用及效用。

方法

为此,我们对大语言模型进行了介绍,概述了其关键特征、能力、局限性、潜在风险以及作为易于使用的软件(如智能手机应用程序)进行部署时的实际考量因素。然后,我们探讨了与痴呆症相关的各个领域,确定了大语言模型在增强理解、诊断和治疗方面的机会,更广泛地侧重于改善患者护理。对于每个领域,都考察了大语言模型的具体贡献,例如它们让用户参与有意义对话、提供个性化支持以及提供认知充实的能力。潜在益处包括改善社交互动、增强认知功能、提高情绪幸福感以及减轻护理人员负担。在护理框架中部署大语言模型也引发了一些担忧和考量。这些包括隐私和安全问题、实证验证的必要性、以用户为中心的设计、适应用户的独特需求以及整合多模态输入以创造更具沉浸感和个性化的体验。此外,必须制定道德准则和隐私协议,以确保大语言模型的负责任和符合道德的部署。

结果

我们报告了一份由痴呆症患者(PwD)及其支持者填写的问卷结果,在问卷中我们调查了大语言模型不同应用场景的效用以及由大语言模型驱动的应用程序应具备的特征。痴呆症患者及其支持者在很大程度上对大语言模型在护理方面的前景持积极态度,尽管对偏差、数据隐私和透明度提出了担忧。

讨论

总体而言,本综述证实了大语言模型通过提高认知能力、丰富社交互动和支持护理人员对痴呆症护理产生积极影响的有前景的应用。研究结果强调了在该领域进一步研发的重要性,以充分利用大语言模型的益处并最大限度地发挥其改善痴呆症患者生活的潜力。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9559/11285660/84dab28e3b1a/frdem-03-1385303-g0001.jpg

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