公开(公告)号：US12040080B2

公开(公告)日：2024-07-16

申请号：US17620445

申请日：2020-09-11

Applicant: Google LLC

Inventor： Robert Carter Dunn ,  Ayush Jain ,  Peggy Yen Phuong Bui ,  Clara Eng ,  David Henry Way ,  Kang Li ,  Vishakha Gupta ,  Jessica Gallegos ,  Dennis Ai ,  Yun Liu ,  David Coz ,  Yuan Liu

IPC: G16H30/40 ,  G16H10/60 ,  G16H50/20

CPC classification number: G16H30/40 ,  G16H10/60 ,  G16H50/20

Abstract: The present disclosure is directed to a deep learning system for differential diagnoses of skin diseases. In particular, the system performs a method that can include obtaining a plurality of images that respectively depict a portion of a patient's skin. The method can include determining, using a machine-learned skin condition classification model, a plurality of embeddings respectively for the plurality of images. The method can include combining the plurality of embeddings to obtain a unified representation associated with the portion of the patient's skin. The method can include determining, using the machine-learned skin condition classification model, a skin condition classification for the portion of the patients skin, the skin condition classification produced by the machine-learned skin condition classification model by processing the unified representation, wherein the skin condition classification identifies one or more skin conditions selected from a plurality of potential skin conditions.

公开(公告)号：US20220359062A1

公开(公告)日：2022-11-10

申请号：US17620445

申请日：2020-09-11

Applicant: Google LLC

Inventor： Robert Carter Dunn ,  Ayush Jain ,  Peggy Yen Phuong Bui ,  Clara Eng ,  David Henry Way ,  Kang Li ,  Vishakha Gupta ,  Jessica Gallegos ,  Dennis Ai ,  Yun Liu ,  David Coz ,  Yuan Liu

IPC: G16H30/40 ,  G16H50/20 ,  G16H10/60

Abstract: The present disclosure is directed to a deep learning system for differential diagnoses of skin diseases. In particular, the system performs a method that can include obtaining a plurality of images that respectively depict a portion of a patient's skin. The method can include determining, using a machine-learned skin condition classification model, a plurality of embeddings respectively for the plurality of images. The method can include combining the plurality of embeddings to obtain a unified representation associated with the portion of the patient's skin. The method can include determining, using the machine-learned skin condition classification model, a skin condition classification for the portion of the patients skin, the skin condition classification produced by the machine-learned skin condition classification model by processing the unified representation, wherein the skin condition classification identifies one or more skin conditions selected from a plurality of potential skin conditions.