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SYSTEMS AND METHODS FOR PREDICTION OF UNNECESSARY EMERGENCY ROOM VISITS

机译:预测不必要的急诊室访问的系统和方法

摘要

A system and method are disclosed for predicting unnecessary emergency room visits based on data collected by a wearable device such as an activity tracker or a smart watch. Artificial Intelligence (AI) algorithms are configured to process an input vector that includes monitored parameter data collected by the wearable device as well as embedding data obtained from health records corresponding to a user account registered to the wearable device. The output of the AI algorithms provides classifiers that represent probabilities that the user of the wearable device is likely to experience one or more acute events within a specific time frame or time frames. The acute event can include an emergency room visit, which may be classified as unnecessary and/or preventable, and the user can be notified directly, via the wearable device or an associated application or technology, to attempt to deter preventable emergency room visits.
机译:公开了一种系统和方法,用于基于由诸如活动跟踪器或智能手表的可穿戴设备收集的数据预测不必要的紧急房间访问。 人工智能(AI)算法被配置为处理包括由可穿戴设备收集的监视的参数数据的输入向量以及从对应于登记到可穿戴设备的用户帐户的健康记录获得的嵌入数据。 AI算法的输出提供了代表可穿戴设备的用户可能在特定时间帧或时间帧内体验一个或多个急性事件的概率的分类器。 急性事件可以包括急诊室访问,该急诊室访问可以被归类为不必要的和/或预防,并且可以通过可穿戴设备或相关的应用或技术直接通知用户,以试图阻止可预防的紧急房间访问。

著录项

  • 公开/公告号US2021407667A1

    专利类型

  • 公开/公告日2021-12-30

    原文格式PDF

  • 申请/专利权人 AETNA INC.;

    申请/专利号US202117362495

  • 申请日2021-06-29

  • 分类号G16H40/67;G16H50/20;G16H10/60;G06F40/40;

  • 国家 US

  • 入库时间 2022-08-24 23:07:17

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