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Machine-Learned Epidemiology

机译:机器学习流行病学

摘要

The present disclosure provides systems and methods that leverage machine-learned models in conjunction with online data to monitor and detect the spread of a disease, such as, for example, a communicable illness. In one example, a computing system can include or otherwise leverage a machine-learned disease detection model. The computing system can input search engine data and, optionally, location data respectively associated with a first plurality of users into the machine-learned disease detection model. The computing system can receive identification of a second plurality of users predicted to have the disease as an output of the machine-learned disease detection model. The second plurality of users can be a subset of the first plurality of users. The computing system can identify one or more locations associated with elevated levels of the disease based at least in part on the location data respectively associated with at least the second plurality of users.
机译:本公开提供了结合机器学习的模型和在线数据来监视和检测疾病(例如,传染病)的传播的系统和方法。在一个示例中,计算系统可以包括或以其他方式利用机器学习的疾病检测模型。该计算系统可以将分别与第一多个用户相关联的搜索引擎数据以及可选的位置数据输入到机器学习的疾病检测模型中。该计算系统可以接收预测为患有该疾病的第二多个用户的标识作为机器学习的疾病检测模型的输出。第二多个用户可以是第一多个用户的子集。该计算系统可以至少部分地基于分别与至少第二多个用户相关联的位置数据来识别与疾病的升高水平相关联的一个或多个位置。

著录项

  • 公开/公告号US2019148023A1

    专利类型

  • 公开/公告日2019-05-16

    原文格式PDF

  • 申请/专利权人 GOOGLE LLC;

    申请/专利号US201815869215

  • 发明设计人 ADAM SADILEK;EVGENIY GABRILOVICH;

    申请日2018-01-12

  • 分类号G16H50/80;G06N99;G06F17/30;

  • 国家 US

  • 入库时间 2022-08-21 12:10:18

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