个人医疗保健数字助理可信度研究综述

IF 23.8 1区 计算机科学 Q1 COMPUTER SCIENCE, THEORY & METHODS ACM Computing Surveys Pub Date : 2025-01-22 DOI:10.1145/3714999
Tania Bailoni, Mauro Dragoni
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引用次数: 0

摘要

人工智能(AI)广泛应用于医疗保健领域。数字健康的一个分支涉及数字助理解决方案的设计和开发。人工智能支持的数字助理强调了值得信赖的必要性,因为它们侵入了人们的生活。此类解决方案旨在提供智能工具,以简化护理路径的管理,或通过监测健康人的生活方式,增强医疗保健组织部署健康预防运动的能力。在这项工作中,我们打算分析有关在数字助理中集成人工智能技术的最新文献。我们专注于过去十年发表的贡献,并对是否以及如何解决值得信赖的支柱进行了仔细的分析。我们还讨论了在设计数字助理时没有考虑值得信赖的支柱的风险,并提出了一些减轻风险的建议。
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A Review on Trustworthiness of Digital Assistants for Personal Healthcare
Artificial Intelligence (AI) is widely used within the healthcare domain. One of the branches of digital health concerns the design and development of digital assistant solutions. AI-enabled digital assistants highlighted the need to be trustworthy given their intrusiveness within people’s lives. Such solutions aim to provide intelligent tools to ease the management of care pathways or to enhance the capabilities of healthcare organizations in deploying health prevention campaigns by monitoring the lifestyles of healthy people. In this work, we intend to analyze the recent literature concerning integrating AI techniques within digital assistants. We focused on the contribution published during the last ten years and we performed a careful analysis of whether and how trustworthy pillars have been addressed. We also discuss the risks of designing digital assistants without considering trustworthy pillars and present some recommendations to mitigate them.
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来源期刊
ACM Computing Surveys
ACM Computing Surveys 工程技术-计算机:理论方法
CiteScore
33.20
自引率
0.60%
发文量
372
审稿时长
12 months
期刊介绍: ACM Computing Surveys is an academic journal that focuses on publishing surveys and tutorials on various areas of computing research and practice. The journal aims to provide comprehensive and easily understandable articles that guide readers through the literature and help them understand topics outside their specialties. In terms of impact, CSUR has a high reputation with a 2022 Impact Factor of 16.6. It is ranked 3rd out of 111 journals in the field of Computer Science Theory & Methods. ACM Computing Surveys is indexed and abstracted in various services, including AI2 Semantic Scholar, Baidu, Clarivate/ISI: JCR, CNKI, DeepDyve, DTU, EBSCO: EDS/HOST, and IET Inspec, among others.
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