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Prescient Profiling - AI driven Volunteer Selection within a Volunteer Notification System

机译:志愿通知系统中的志愿志愿者选择

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A Volunteer Notification System (VNS) is a promising approach to integrate laypersons into emergency medical services (EMS). In case of a medical emergency, a VNS will alarm those potential helpers who can arrive on scene fast enough to provide the most urgent measures until the professional helpers arrive at the victim. Whereas the basic requirements and criteria of a VNS have been discussed in recent publications, this paper will focus on the actual volunteer selection process and the underlying concept of Prescient Profiling. By using concepts of artificial intelligence, the available data is processed in order to generate an abstract digital representation of a volunteer and further enhanced to produce individual user profiles. These profiles will enable predictions on future decisions and the identification of behavioral patterns within the pool of volunteers. The goal is to provide an efficient algorithm for determining a highly sophisticated set of relevant volunteers for an ongoing medical emergency.
机译:志愿者通知系统(VNS)是一项有希望的方法,将拉德龙纳入紧急医疗服务(EMS)。在医疗紧急情况下,VNS将警告那些可以快速到达现场的潜在助手,以便在专业帮助者到达受害者之前提供最紧急的措施。虽然在最近的出版物中讨论了VNS的基本要求和标准,但本文将重点关注实际的志愿选择过程和潜在的现状概念。通过使用人工智能的概念,处理可用数据以便生成志愿者的抽象数字表示,并进一步增强以产生单独的用户配置文件。这些简档将能够预测对未来的决策和识别志愿者池内的行为模式。目标是提供一种有效的算法,用于确定高度复杂的相关志愿者,以便进行正在进行的医疗紧急情况。

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