Artificial Intelligence for Participatory Health: Applications, Impact, and Future Implications.
Artificial Intelligence for Participatory Health: Applications, Impact, and Future Implications.
复制标题
DOI：
10.1055/s-0039-1677902
复制
发表时间：
2019-08-01
影响因子：
--
通讯作者：
Merolli, Mark
中科院分区：
文献类型：
--
作者：
Denecke, Kerstin;Gabarron, Elia;Merolli, Mark
目的：人工智能（AI）为参与式健康信息学领域的工作人员和专业人员提供了从各种在线来源获得强大见解的机会。本文的目的是确定目前的艺术和应用领域的AI参与health.METHODS的背景下进行了搜索，在7个数据库（PubMed，Embase，CINAHL，PsychInfo，ACM数字图书馆，IEEExplore，和SCOPUS），自2013年以来发表的文章。此外，临床试验涉及AI在参与性健康环境中注册在clinicaltrials.gov进行了收集和analyzed.RESULTS：22篇文章和12个试验被选中进行审查。人工智能在参与式健康中最常见的应用是对社交媒体数据的二次分析：自我报告的数据，包括患者在医疗机构的经历，药物不良反应的报告，非处方药的安全性和有效性问题，以及对药物的其他观点。其他应用领域包括确定哪些在线论坛线程需要版主帮助，识别可能退出论坛的用户，提取在线论坛中使用的术语以学习其词汇，突出显示在线问题和答案中缺少的上下文信息，以及为消费者解释技术医学术语。虽然支持参与式健康的人工智能仍处于起步阶段，但为了推动该领域的发展，应该考虑一些重要的研究重点。进一步研究评估人工智能在参与式健康信息学中对个人心理社会健康的影响，将有助于促进人工智能更广泛地被接受到医疗保健生态系统中。
OBJECTIVE: Artificial intelligence (AI) provides people and professionals working in the field of participatory health informatics an opportunity to derive robust insights from a variety of online sources. The objective of this paper is to identify current state of the art and application areas of AI in the context of participatory health.METHODS: A search was conducted across seven databases (PubMed, Embase, CINAHL, PsychInfo, ACM Digital Library, IEEExplore, and SCOPUS), covering articles published since 2013. Additionally, clinical trials involving AI in participatory health contexts registered at clinicaltrials.gov were collected and analyzed.RESULTS: Twenty-two articles and 12 trials were selected for review. The most common application of AI in participatory health was the secondary analysis of social media data: self-reported data including patient experiences with healthcare facilities, reports of adverse drug reactions, safety and efficacy concerns about over-the-counter medications, and other perspectives on medications. Other application areas included determining which online forum threads required moderator assistance, identifying users who were likely to drop out from a forum, extracting terms used in an online forum to learn its vocabulary, highlighting contextual information that is missing from online questions and answers, and paraphrasing technical medical terms for consumers.CONCLUSIONS: While AI for supporting participatory health is still in its infancy, there are a number of important research priorities that should be considered for the advancement of the field. Further research evaluating the impact of AI in participatory health informatics on the psychosocial wellbeing of individuals would help in facilitating the wider acceptance of AI into the healthcare ecosystem.