公开(公告)号：US20240394871A1

公开(公告)日：2024-11-28

申请号：US18261462

申请日：2022-08-26

Applicant: BOE TECHNOLOGY GROUP CO., LTD.

Inventor： Cuifang Zhang ,  Zhenzhong Zhang ,  Yulan Hu ,  Shuobin Liang ,  Xiaotian Jiang

IPC: G06T7/00 ,  G06T7/11 ,  G06T7/174 ,  G06V10/26 ,  G06V10/77 ,  G06V10/774 ,  G06V10/80

Abstract: The present disclosure provides Aa computer-implemented method, a method of training a deep learning model, an electronic device, and a medium are provided. The method includes: obtaining a target image segmentation result according to a target medical image of a target part, wherein the target medical image includes a medical image in at least one modality; obtaining target fusion data according to the target medical image segmentation result and a medical image in a predetermined modality in the target medical image; and obtaining a target multi-mutation detection result according to the target fusion data.

公开(公告)号：US12198454B2

公开(公告)日：2025-01-14

申请号：US17513473

申请日：2021-10-28

Applicant: BOE TECHNOLOGY GROUP CO., LTD.

Inventor： Xue Chen ,  Jinnv Liu ,  Yude Li ,  Xianqiang Ni ,  Shuobin Liang ,  Li Zhou

IPC: G06V20/64 ,  A61B5/30 ,  A61B5/308 ,  G06F18/2137 ,  G06F18/214 ,  G06F18/241 ,  G06V10/147 ,  G06V10/42 ,  G06V10/94 ,  G16H10/60 ,  G16H50/20

Abstract: An attention mechanism-based 12-lead electrocardiogram (ECG) classification method is described, the method including acquiring an original image of a 12-lead ECG, segmenting waveform data recorded in the original image to obtain segmented waveform data for each lead in the 12-lead ECG, performing depth feature extraction on the segmented waveform data of said each lead to obtain a first feature map of said each lead, performing feature transformation on the first feature map of said each lead based on an attention mechanism to obtain a depth feature of said each lead, and classifying the depth feature of said each lead to obtain a classification result for the original image. The classification method can make full use of the 12-lead ECG for overall classification and improve the accuracy of image classification.

公开(公告)号：US20240371518A1

公开(公告)日：2024-11-07

申请号：US18247590

申请日：2022-05-27

Applicant: BOE TECHNOLOGY GROUP CO., LTD.

Inventor： Sifan Wang ,  Shuobin Liang

IPC: G16H50/20 ,  G16H70/40

Abstract: The present disclosure provides a method and an apparatus for predicting a relevance degree, and a method and an apparatus for training a machine learning model. The method for predicting a relevance degree includes constructing a heterogeneous matrix; processing the feature vector of the each medication and the feature vector of the each disease by using a first machine learning model to obtain a first predicted value of the relevance degree between the each medication and the each disease; processing the heterogeneous matrix by using a second machine learning model to obtain a relevance degree matrix; and obtaining a predicted result of the relevance degree between the each medication and the each disease according to the first predicted value of the relevance degree and the second predicted value of the relevance degree between the each medication and the each disease.

公开(公告)号：US11892424B2

公开(公告)日：2024-02-06

申请号：US17486837

申请日：2021-09-27

Applicant: Beijing BOE Technology Development Co., Ltd. ,  BOE Technology Group Co., Ltd.

Inventor： Kui Liang ,  Shuobin Liang

IPC: G01N27/327 ,  H01B3/30 ,  H01B17/64

CPC classification number: G01N27/327 ,  H01B3/306 ,  H01B17/64

Abstract: The present disclosure provides a biological detection device, a biological chip, a microelectrode structure, and a manufacturing method of the microelectrode structure. The microelectrode structure can include a first insulating layer, a protrusion, and an electrode layer. The protrusion is disposed on the first insulating layer. The electrode layer conformally covers the first insulating layer and the protrusion. The present disclosure can improve the detection accuracy.