精准艾滋病毒健康应用程序,积极的同伴,由数据利用,人工智能和学习驱动

Golnoush Asaeikheybari, Cory Hughart, Devansh Gupta, A. Avery, Mary M. Step, Jennifer McMillen Smith, Joshua Kratz, Julia Briggs, Ming-chun Huang
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引用次数: 2

摘要

移动电话应用程序为提供量身定制的人类免疫缺陷病毒(HIV)和性传播疾病(STD)预防和护理提供了一个新的、易于访问的平台。最近的研究表明,流动干预措施在护理方案、抗逆转录病毒治疗(ART)、疾病自我管理方面具有积极作用,并且在减少艾滋病毒流行和污名化方面也至关重要。在本文中,通过数据利用、人工智能(Al)和学习,协作开发了一款精确健康应用程序Positive Peers (PP)。Positive Peers是一款基于Android/ ios的社交媒体应用程序,为强烈需要支持和激励的年轻成年艾滋病毒感染者亚群提供支持和信息。我们采用结合自然语言处理(NLP)的干预方法来帮助目标青少年更多地参与应用程序。使用NLP促进信息流动,通过注入有用的相关信息,在减少患者的不确定性方面发挥关键作用。它进一步提高了应用程序用户的交互性,同时为用户提供了一个紧凑的平台,以便更好地找到他们的问题和关注点的答案。NLP系统已经在alpha测试中进行了评估。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Precision HIV Health App, Positive Peers, Powered by Data Harnessing, AI, and Learning
Mobile phone applications provide a new and easy-access platform for delivering tailored human immunodeficiency virus (HIV) and sexually transmitted disease (STD) prevention and care. Recent researches have shown that mobile interventions have positive effects in adhesive to care program, antiretroviral therapy (ART), self-management of disease, and are also critical in decreasing the HIV pandemic, and stigmatization. In this paper, a precision health app, Positive Peers (PP), has been developed collaboratively while enabled by data harnessing, Artificial Intelligence (Al), and learning. Positive Peers is an Android/iOS-based social media app for providing support and information to a young adult subgroup living with HIV who are in strong need of support and motivation. We apply an intervention approach combined with Natural Language Processing (NLP) to help the targeted youth to engage more with the app. Using NLP facilitates the flow of information that has a critical role in decreasing the uncertainty of patients by being injected to useful related information. It further improves the interaction of users of the app while providing a compact platform for users to better find the answers to their questions and concerns. The NLP system has been evaluated in an alpha test.
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