公开(公告)号：US11972350B2

公开(公告)日：2024-04-30

申请号：US18165021

申请日：2023-02-06

Applicant: Google LLC

Inventor： Ming Jack Po ,  Christopher Co ,  Katherine Chou

IPC: G06N3/08 ,  G06N5/022 ,  G06Q50/22 ,  G16H50/20

CPC classification number: G06N3/08 ,  G06N5/022 ,  G06Q50/22 ,  G16H50/20

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.

公开(公告)号：US20230186090A1

公开(公告)日：2023-06-15

申请号：US18165021

申请日：2023-02-06

Applicant: Google LLC

Inventor： Ming Jack Po ,  Christopher Co ,  Katherine Chou

IPC: G06N3/08 ,  G06N5/022 ,  G16H50/20 ,  G06Q50/22

CPC classification number: G06N3/08 ,  G06N5/022 ,  G16H50/20 ,  G06Q50/22

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.

公开(公告)号：US20240242077A1

公开(公告)日：2024-07-18

申请号：US18618587

申请日：2024-03-27

Applicant: Google LLC

Inventor： Ming Jack Po ,  Christopher Co ,  Katherine Chou

IPC: G06N3/08 ,  G06N5/022 ,  G06Q50/22 ,  G16H50/20

CPC classification number: G06N3/08 ,  G06N5/022 ,  G06Q50/22 ,  G16H50/20

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.

公开(公告)号：US20230277069A1

公开(公告)日：2023-09-07

申请号：US18011899

申请日：2022-03-03

Applicant: Google LLC

Inventor： Jiening Zhan ,  Sean Kyungmok Bae ,  Silviu Borac ,  Yunus Emre ,  Jonathan Wesor Wang ,  Jiang Wu ,  Mehr Kashyap ,  Ming Jack Po ,  Liwen Chen ,  Melissa Chung ,  John Cannon ,  Eric Steven Teasley ,  James Alexander Taylor, Jr. ,  Michael Vincent McConnell ,  Alejandra Maciel ,  Allen KC Chai ,  Shwetak Patel ,  Gregory Sean Corrado ,  Si-Hyuck Kang ,  Yun Liu ,  Michael Rubinstein ,  Michael Spencer Krainin ,  Neal Wadhwa

IPC: A61B5/0205 ,  A61B5/00

CPC classification number: A61B5/0205 ,  A61B5/0077 ,  A61B5/725 ,  A61B5/6898 ,  A61B5/7257 ,  A61B5/7278 ,  A61B5/7485 ,  A61B5/0816

Abstract: Generally, the present disclosure is directed to systems and methods for measuring heart rate and respiratory rate using a camera such as, for example, a smartphone camera or other consumer-grade camera. Specifically, the present disclosure presents and validates two algorithms that make use of smartphone cameras (or the like) for measuring heart rate (HR) and respiratory rate (RR) for consumer wellness use. As an example, HR can be measured by placing the finger of a subject over the rear-facing camera. As another example, RR can be measured via a video of the subject sitting still in front of the front-facing camera.

公开(公告)号：US11574191B2

公开(公告)日：2023-02-07

申请号：US16905219

申请日：2020-06-18

Applicant: Google LLC

Inventor： Ming Jack Po ,  Christopher Co ,  Katherine Chou

IPC: G06N3/08 ,  G06N5/02 ,  G16H50/20 ,  G06Q50/22

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.