公开(公告)号：US20190034589A1

公开(公告)日：2019-01-31

申请号：US15690703

申请日：2017-08-30

Applicant: Google Inc.

Inventor： Kai Chen ,  Patrik Sundberg ,  Alexander Mossin ,  Nissan Hajaj ,  Kurt Litsch ,  James Wexler ,  Yi Zhang ,  Kun Zhang ,  Jacob Marcus ,  Eyal Oren ,  Hector Yee ,  Jeffrey Dean ,  Michaela Hardt ,  Benjamin Irvine ,  James Wilson ,  Andrew Dai ,  Peter Liu ,  Xiaomi Sun ,  Quoc Le ,  Xiaobing Liu ,  Alvin Rajkomar ,  Gregory Corrado ,  Gerardo Flores ,  Yingwei Cui ,  Gavin Duggan

IPC: G06F19/00 ,  G06N3/08 ,  G06N3/04

Abstract: A system for predicting and summarizing medical events from electronic health records includes a computer memory storing aggregated electronic health records from a multitude of patients of diverse age, health conditions, and demographics including medications, laboratory values, diagnoses, vital signs, and medical notes. The aggregated electronic health records are converted into a single standardized data structure format and ordered arrangement per patient, e.g., into a chronological order. A computer (or computer system) executes one or more deep learning models trained on the aggregated health records to predict one or more future clinical events and summarize pertinent past medical events related to the predicted events on an input electronic health record of a patient having the standardized data structure format and ordered into a chronological order. An electronic device configured with a healthcare provider-facing interface displays the predicted one or more future clinical events and the pertinent past medical events of the patient.

公开(公告)号：US20170171620A1

公开(公告)日：2017-06-15

申请号：US15015972

申请日：2016-02-04

Applicant: Google Inc.

Inventor： Eyal Oren ,  Farzan Rohani

IPC: H04N21/466 ,  H04N21/45 ,  H04N21/258 ,  H04N21/25

CPC classification number: H04N21/4667 ,  G06Q30/02 ,  H04N21/252 ,  H04N21/2543 ,  H04N21/25866 ,  H04N21/44213 ,  H04N21/44218 ,  H04N21/44222 ,  H04N21/4532 ,  H04N21/658 ,  H04N21/6582

Abstract: The present disclosure provides systems and methods for estimating audience member engagement with content, or distinguishing between users consuming content and users who have become distracted or have left. User presence or attention may be estimated from user interactions with or skipping of content, with the user interactions either compared to high quality engagement data from small audience measurement panels, or extrapolated based on a temporal-engagement curve. An attention gap may be estimated, representing users that were not present for or not engaged with or paying attention to a presentation of content at a client device. This allows the measurement system to distinguish between users who consumed and potentially enjoyed the content, and users who did not, even as client devices of both sets of users receive and present the content items.

公开(公告)号：US10405045B2

公开(公告)日：2019-09-03

申请号：US15015972

申请日：2016-02-04

Applicant: Google Inc.

Inventor： Eyal Oren ,  Farzan Rohani

IPC: H04N21/466 ,  H04N21/658 ,  H04N21/442 ,  H04N21/2543 ,  H04N21/25 ,  H04N21/45 ,  H04N21/258 ,  G06Q30/02

Abstract: The present disclosure provides systems and methods for estimating audience member engagement with content, or distinguishing between users consuming content and users who have become distracted or have left. User presence or attention may be estimated from user interactions with or skipping of content, with the user interactions either compared to high quality engagement data from small audience measurement panels, or extrapolated based on a temporal-engagement curve. An attention gap may be estimated, representing users that were not present for or not engaged with or paying attention to a presentation of content at a client device. This allows the measurement system to distinguish between users who consumed and potentially enjoyed the content, and users who did not, even as client devices of both sets of users receive and present the content items.

公开(公告)号：US10225612B2

公开(公告)日：2019-03-05

申请号：US15015972

申请日：2016-02-04

Applicant: Google Inc.

Inventor： Eyal Oren ,  Farzan Rohani

IPC: H04N21/466 ,  H04N21/658 ,  H04N21/442 ,  H04N21/2543 ,  H04N21/25 ,  H04N21/45 ,  H04N21/258 ,  G06Q30/02

Abstract: The present disclosure provides systems and methods for estimating audience member engagement with content, or distinguishing between users consuming content and users who have become distracted or have left. User presence or attention may be estimated from user interactions with or skipping of content, with the user interactions either compared to high quality engagement data from small audience measurement panels, or extrapolated based on a temporal-engagement curve. An attention gap may be estimated, representing users that were not present for or not engaged with or paying attention to a presentation of content at a client device. This allows the measurement system to distinguish between users who consumed and potentially enjoyed the content, and users who did not, even as client devices of both sets of users receive and present the content items.

公开(公告)号：US20190034591A1

公开(公告)日：2019-01-31

申请号：US15690721

申请日：2017-08-30

Applicant: Google Inc.

Inventor： Alexander Mossin ,  Alvin Rajkomar ,  Eyal Oren ,  James Wilson ,  James Wexler ,  Patrik Sundberg ,  Andrew Dai ,  Yingwei Cui ,  Gregory Corrado ,  Hector Yee ,  Jacob Marcus ,  Jeffrey Dean ,  Benjamin Irvine ,  Kai Chen ,  Kun Zhang ,  Michaela Hardt ,  Xiaomi Sun ,  Nissan Hajaj ,  Peter Liu ,  Quoc Le ,  Xiaobing Liu ,  Yi Zhang

IPC: G06F19/00 ,  G06N3/08 ,  G06N3/04

Abstract: A system for predicting and summarizing medical events from electronic health records includes a computer memory storing aggregated electronic health records from a multitude of patients of diverse age, health conditions, and demographics including medications, laboratory values, diagnoses, vital signs, and medical notes. The aggregated electronic health records are converted into a single standardized data structure format and ordered arrangement per patient, e.g., into a chronological order. A computer (or computer system) executes one or more deep learning models trained on the aggregated health records to predict one or more future clinical events and summarize pertinent past medical events related to the predicted events on an input electronic health record of a patient having the standardized data structure format and ordered into a chronological order. An electronic device configured with a healthcare provider-facing interface displays the predicted one or more future clinical events and the pertinent past medical events of the patient.

公开(公告)号：US20190034590A1

公开(公告)日：2019-01-31

申请号：US15690714

申请日：2017-08-30

Applicant: Google Inc.

Inventor： Eyal Oren ,  Yingwei Cui ,  Gerardo Flores ,  Gavin Duggan ,  Kun Zhang ,  Kurt Litsch ,  Patrik Sundberg ,  Yi Zhang

IPC: G06F19/00 ,  G06N3/08

Abstract: A system for predicting and summarizing medical events from electronic health records includes a computer memory storing aggregated electronic health records from a multitude of patients of diverse age, health conditions, and demographics including medications, laboratory values, diagnoses, vital signs, and medical notes. The aggregated electronic health records are converted into a single standardized data structure format and ordered arrangement per patient, e.g., into a chronological order. A computer (or computer system) executes one or more deep learning models trained on the aggregated health records to predict one or more future clinical events and summarize pertinent past medical events related to the predicted events on an input electronic health record of a patient having the standardized data structure format and ordered into a chronological order. An electronic device configured with a healthcare provider-facing interface displays the predicted one or more future clinical events and the pertinent past medical events of the patient.