公开(公告)号：US20250157201A1

公开(公告)日：2025-05-15

申请号：US19020516

申请日：2025-01-14

Applicant: Google LLC

Inventor： Arunachalam Narayanaswamy ,  Subhashini Venugopalan ,  Avinash Vaidyanathan Varadarajan

IPC: G06V10/776 ,  G06V10/82

Abstract: Systems and methods for identifying visual features that influence a predictive model are provided. The technology employs an image translation function to introduce a visual feature into an image to create a modified image that can be fed to a predictive model. When the predictive model generates a different prediction for a given image than it does for a modified version of that image, the image translation function can then be used to make further modified versions that exaggerate the introduced visual feature. The technology thus aids in identifying visual features that influence the predictive model so that the model's conclusions can be understood, and so that those visual features can be further studied and tested.

公开(公告)号：US20240265294A1

公开(公告)日：2024-08-08

申请号：US18156915

申请日：2023-01-19

Applicant: Google LLC

Inventor： Badih Ghazi ,  Pritish Kamath ,  Shanmugasundaram Ravikumar ,  Ethan Jacob Leeman ,  Pasin Manurangsi ,  Avinash Vaidyanathan Varadarajan ,  Chiyuan Zhang

IPC: G06N20/00

CPC classification number: G06N20/00

Abstract: An example method is provided for conducting differentially private communication of training data for training a machine-learned model. Initial label data can be obtained that corresponds to feature data. A plurality of label bins can be determined to respectively provide representative values for initial label values assigned to the plurality of label bins. Noised label data can be generated, based on a probability distribution over the plurality of label bins, to correspond to the initial label data, the probability distribution characterized by, for a respective noised label corresponding to a respective initial label of the initial label data, a first probability for returning a representative value of a label bin to which the respective initial label is assigned, and a second probability for returning another value. The noised label data can be communicated for training the machine-learned model.

公开(公告)号：US11823385B2

公开(公告)日：2023-11-21

申请号：US17838971

申请日：2022-06-13

Applicant: Google LLC

Inventor： Christopher Semturs ,  Dale R. Webster ,  Avinash Vaidyanathan Varadarajan ,  Akinori Mitani ,  Lily Hao Yi Peng

IPC: G06K9/00 ,  G06T7/00 ,  G16H10/60 ,  G06N3/04

CPC classification number: G06T7/0012 ,  G06N3/04 ,  G16H10/60 ,  G06T2207/20081 ,  G06T2207/20084 ,  G06T2207/30101

Abstract: Methods, systems, and apparatus, including computer programs encoded on computer storage media, for processing fundus images using fundus image processing machine learning models.

公开(公告)号：US11636601B2

公开(公告)日：2023-04-25

申请号：US17212811

申请日：2021-03-25

Applicant: GOOGLE LLC

Inventor： Lily Hao Yi Peng ,  Dale R. Webster ,  Philip Charles Nelson ,  Varun Gulshan ,  Marc Adlai Coram ,  Martin Christian Stumpe ,  Derek Janme Wu ,  Arunachalam Narayanaswamy ,  Avinash Vaidyanathan Varadarajan ,  Katharine Blumer ,  Yun Liu ,  Ryan Poplin

IPC: G06T7/00 ,  G16H50/30 ,  G16H50/20 ,  G06N3/04 ,  G06N3/08

Abstract: Methods, systems, and apparatus, including computer programs encoded on computer storage media, for processing fundus images using fundus image processing machine learning models. One of the methods includes obtaining a model input comprising one or more fundus images, each fundus image being an image of a fundus of an eye of a patient; processing the model input using a fundus image processing machine learning model, wherein the fundus image processing machine learning model is configured to process the model input comprising the one or more fundus image to generate a model output; and processing the model output to generate health analysis data.

公开(公告)号：US20200311933A1

公开(公告)日：2020-10-01

申请号：US16835152

申请日：2020-03-30

Applicant: Google LLC

Inventor： Christopher Semturs ,  Dale R. Webster ,  Avinash Vaidyanathan Varadarajan ,  Akinori Mitani ,  Lily Hao Yi Peng

IPC: G06T7/00 ,  G16H10/60 ,  G06N3/04

Abstract: Methods, systems, and apparatus, including computer programs encoded on computer storage media, for processing fundus images using fundus image processing machine learning models.

公开(公告)号：US20230230232A1

公开(公告)日：2023-07-20

申请号：US18011597

申请日：2021-11-02

Applicant: Google LLC

Inventor： Yun Liu ,  Naama Hammel ,  Akinori Mitani ,  Derek Janme Wu ,  Ashish Dilipchand Bora ,  Avinash Vaidyanathan Varadarajan ,  Boris Alekandrovich Babenko

IPC: G06T7/00 ,  G16H50/50 ,  G16H30/40 ,  A61B3/12

CPC classification number: G06T7/0012 ,  G16H50/50 ,  G16H30/40 ,  A61B3/1241 ,  G06T2207/30041 ,  G06T2207/20081 ,  G06T2207/20084

Abstract: The present disclosure is directed to systems and methods that leverage machine learning for detection of eye or non-eye (e.g., systemic) diseases from external anterior eye images. In particular, a computing system can include and use one or more machine-learned disease detection models to provide disease predictions for a patient based on external anterior eye images of the patient. Specifically, in some example implementations, a computing system can obtain one or more external images that depict an anterior portion of an eye of a patient. The computing system can process the one or more external images with the one or more machine-learned disease detection models to generate a disease prediction for the patient relative to one or more diseases, including, as examples, diseases which present manifestations in a posterior of the eye (e.g., diabetic retinopathy) or systemic diseases (e.g., poorly controlled diabetes).

公开(公告)号：US11361435B2

公开(公告)日：2022-06-14

申请号：US16835152

申请日：2020-03-30

Applicant: Google LLC

Inventor： Christopher Semturs ,  Dale R. Webster ,  Avinash Vaidyanathan Varadarajan ,  Akinori Mitani ,  Lily Hao Yi Peng

IPC: G06K9/00 ,  G06T7/00 ,  G16H10/60 ,  G06N3/04

Abstract: Methods, systems, and apparatus, including computer programs encoded on computer storage media, for processing fundus images using fundus image processing machine learning models.

公开(公告)号：US10970841B2

公开(公告)日：2021-04-06

申请号：US16325580

申请日：2017-08-18

Applicant: GOOGLE LLC

Inventor： Lily Hao Yi Peng ,  Dale R. Webster ,  Philip Charles Nelson ,  Varun Gulshan ,  Marc Adlai Coram ,  Martin Christian Stumpe ,  Derek Janme Wu ,  Arunachalam Narayanaswamy ,  Avinash Vaidyanathan Varadarajan ,  Katharine Blumer ,  Yun Liu ,  Ryan Poplin

IPC: G06T7/00 ,  G16H50/30 ,  G16H50/20 ,  G06N3/04 ,  G06N3/08

Abstract: Methods, systems, and apparatus, including computer programs encoded on computer storage media, for processing fundus images using fundus image processing machine learning models. One of the methods includes obtaining a model input comprising one or more fundus images, each fundus image being an image of a fundus of an eye of a patient; processing the model input using a fundus image processing machine learning model, wherein the fundus image processing machine learning model is configured to process the model input comprising the one or more fundus image to generate a model output; and processing the model output to generate health analysis data.

公开(公告)号：US12230016B2

公开(公告)日：2025-02-18

申请号：US17799740

申请日：2020-03-03

Applicant: Google LLC

Inventor： Arunachalam Narayanaswamy ,  Subhashini Venugopalan ,  Avinash Vaidyanathan Varadarajan

IPC: G06V10/776 ,  G06V10/82

Abstract: Systems and methods for identifying visual features that influence a predictive model are provided. The technology employs an image translation function to introduce a visual feature into an image to create a modified image that can be fed to a predictive model. When the predictive model generates a different prediction for a given image than it does for a modified version of that image, the image translation function can then be used to make further modified versions that exaggerate the introduced visual feature. The technology thus aids in identifying visual features that influence the predictive model so that the model's conclusions can be understood, and so that those visual features can be further studied and tested.

公开(公告)号：US20230260126A1

公开(公告)日：2023-08-17

申请号：US18305789

申请日：2023-04-24

Applicant: Google LLC

Inventor： Lily Hao Yi Peng ,  Dale R. Webster ,  Philip Charles Nelson ,  Varun Gulshan ,  Marc Adlai Coram ,  Martin Christian Stumpe ,  Derek Janme Wu ,  Arunachalam Narayanaswamy ,  Avinash Vaidyanathan Varadarajan ,  Katharine Blumer ,  Yun Liu ,  Ryan Poplin

IPC: G06T7/00 ,  G16H50/30 ,  G16H50/20 ,  G06N3/044 ,  G06N3/08

CPC classification number: G06T7/0016 ,  G16H50/30 ,  G16H50/20 ,  G06N3/044 ,  G06N3/08 ,  G01N2800/168 ,  G01N2800/164 ,  G06T2207/10016 ,  G06T2207/20076 ,  G06T2207/20081 ,  G06T2207/30041

Abstract: Methods, systems, and apparatus, including computer programs encoded on computer storage media, for processing fundus images using fundus image processing machine learning models. One of the methods includes obtaining a model input comprising one or more fundus images, each fundus image being an image of a fundus of an eye of a patient; processing the model input using a fundus image processing machine learning model, wherein the fundus image processing machine learning model is configured to process the model input comprising the one or more fundus image to generate a model output; and processing the model output to generate health analysis data.