Generating templated documents using machine learning techniques

    公开(公告)号:US10691998B2

    公开(公告)日:2020-06-23

    申请号:US15385804

    申请日:2016-12-20

    Applicant: Google Inc.

    Abstract: Systems and methods of predicting documentation associated with an encounter between attendees are provided. For instance, attendee data indicative of one or more previous visit notes associated with a first attendee can be obtained. The attendee data can be inputted into a machine-learned note prediction model that includes a neural network. The neural network can generate one or more context vectors descriptive of the attendee data. Data indicative of a predicted visit note can be received as output of the machine-learned note prediction model based at least in part on the context vectors. The predicted visit note can include a set of predicted information expected to be included in a subsequently generated visit note associated with the first attendee.

    GENERATING TEMPLATED DOCUMENTS USING MACHINE LEARNING TECHNIQUES

    公开(公告)号:US20180174043A1

    公开(公告)日:2018-06-21

    申请号:US15385804

    申请日:2016-12-20

    Applicant: Google Inc.

    Abstract: Systems and methods of predicting documentation associated with an encounter between attendees are provided. For instance, attendee data indicative of one or more previous visit notes associated with a first attendee can be obtained. The attendee data can be inputted into a machine-learned note prediction model that includes a neural network. The neural network can generate one or more context vectors descriptive of the attendee data. Data indicative of a predicted visit note can be received as output of the machine-learned note prediction model based at least in part on the context vectors. The predicted visit note can include a set of predicted information expected to be included in a subsequently generated visit note associated with the first attendee.

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