公开(公告)号：US11954902B2

公开(公告)日：2024-04-09

申请号：US17114586

申请日：2020-12-08

Applicant: Google LLC

Inventor： Jeffrey De Fauw ,  Joseph R. Ledsam ,  Bernardino Romera-Paredes ,  Stanislav Nikolov ,  Nenad Tomasev ,  Samuel Blackwell ,  Harry Askham ,  Xavier Glorot ,  Balaji Lakshminarayanan ,  Trevor Back ,  Mustafa Suleyman ,  Pearse A. Keane ,  Olaf Ronneberger ,  Julien Robert Michel Cornebise

IPC: G06V10/82 ,  G06F18/21 ,  G06F18/2413 ,  G06F18/25 ,  G06T7/00 ,  G06T11/00 ,  G06V10/44 ,  G06V10/764 ,  G06V10/80

CPC classification number: G06V10/82 ,  G06F18/217 ,  G06F18/24133 ,  G06F18/254 ,  G06T7/0012 ,  G06T11/003 ,  G06V10/454 ,  G06V10/764 ,  G06V10/809 ,  G06T2207/10101 ,  G06T2207/20081 ,  G06T2207/20084 ,  G06T2207/30041 ,  G06V2201/03

Abstract: Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for generating a final classification output for an image of eye tissue. The image is provided as input to each of one or more segmentation neural networks to obtain one or more segmentation maps of the eye tissue in the image. A respective classification input is generated from each of the segmentation maps. For each of the segmentation maps, the classification input for the segmentation map is provided as input to each of one or more classification neural networks to obtain, for each segmentation map, a respective classification output from each classification neural network. A final classification output for the image is generated from the respective classification outputs for each of the segmentation maps.

公开(公告)号：US11302446B2

公开(公告)日：2022-04-12

申请号：US16683139

申请日：2019-11-13

Applicant: Google LLC

Inventor： Nenad Tomasev ,  Xavier Glorot ,  Jack William Rae ,  Michal Zielinski ,  Anne Mottram ,  Harry Askham ,  Andre Saraiva Nobre Dos Santos ,  Clemens Ludwig Meyer ,  Suman Ravuri ,  Ivan Protsyuk ,  Trevor Back ,  Joseph R. Ledsam ,  Shakir Mohamed

IPC: G16H50/30 ,  G16H70/60 ,  G16H50/50 ,  G16H10/60 ,  G06N3/08

Abstract: Methods, systems, and apparatus, including computer programs encoded on computer storage media, for predicting future adverse health events using neural networks. One of the methods includes receiving electronic health record data for a patient; generating, from the electronic health record data, an input sequence comprising a respective feature representation at each of a plurality of time window time steps, comprising, for each time window time step: determining, for each of the possible numerical features, whether the numerical feature occurred during the time window; and generating, for each of the possible numerical features, one or more presence features that identify whether the numerical feature occurred during the time window; and processing the input sequence using a neural network to generate a neural network output that characterizes a predicted likelihood that an adverse health event will occur to the patient.

公开(公告)号：US20200152333A1

公开(公告)日：2020-05-14

申请号：US16683139

申请日：2019-11-13

Applicant: Google LLC

Inventor： Nenad Tomasev ,  Xavier Glorot ,  Jack William Rae ,  Michal Zielinski ,  Anne Mottram ,  Harry Askham ,  Andre Saraiva Nobre Dos Santos ,  Clemens Ludwig Meyer ,  Suman Ravuri ,  Ivan Protsyuk ,  Trevor Back ,  Joseph R. Ledsam ,  Shakir Mohamed

IPC: G16H50/30 ,  G16H10/60 ,  G16H50/50 ,  G16H70/60 ,  G06N3/08

Abstract: Methods, systems, and apparatus, including computer programs encoded on computer storage media, for predicting future adverse health events using neural networks. One of the methods includes receiving electronic health record data for a patient; generating, from the electronic health record data, an input sequence comprising a respective feature representation at each of a plurality of time window time steps, comprising, for each time window time step: determining, for each of the possible numerical features, whether the numerical feature occurred during the time window; and generating, for each of the possible numerical features, one or more presence features that identify whether the numerical feature occurred during the time window; and processing the input sequence using a neural network to generate a neural network output that characterizes a predicted likelihood that an adverse health event will occur to the patient.

公开(公告)号：US20210118198A1

公开(公告)日：2021-04-22

申请号：US17114586

申请日：2020-12-08

Applicant: Google LLC

Inventor： Jeffrey De Fauw ,  Joseph R. Ledsam ,  Bernardino Romera-Paredes ,  Stanislav Nikolov ,  Nenad Tomasev ,  Samuel Blackwell ,  Harry Askham ,  Xavier Glorot ,  Balaji Lakshminarayanan ,  Trevor Back ,  Mustafa Suleyman ,  Pearse A. Keane ,  Olaf Ronneberger ,  Julien Robert Michel Cornebise

IPC: G06T11/00 ,  G06K9/62 ,  G06K9/46 ,  G06T7/00

Abstract: Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for generating a final classification output for an image of eye tissue. The image is provided as input to each of one or more segmentation neural networks to obtain one or more segmentation maps of the eye tissue in the image. A respective classification input is generated from each of the segmentation maps. For each of the segmentation maps, the classification input for the segmentation map is provided as input to each of one or more classification neural networks to obtain, for each segmentation map, a respective classification output from each classification neural network. A final classification output for the image is generated from the respective classification outputs for each of the segmentation maps.