公开(公告)号：US11704803B2

公开(公告)日：2023-07-18

申请号：US17218052

申请日：2021-03-30

申请人： The Board of Trustees of the Leland Stanford Junior University

发明人： David Ouyang ,  Bryan He ,  James Zou ,  Euan A. Ashley

IPC分类号： G06K9/00 ,  G06T7/10

CPC分类号： G06T7/10 ,  G06T2207/10016 ,  G06T2207/10132 ,  G06T2207/20081 ,  G06T2207/30048 ,  G06T2207/30104

摘要： Various embodiments are directed to video-based deep learning evaluation of cardiac ultrasound that accurately identify cardiomyopathy and predict ejection fraction, the most common metric of cardiac function. Embodiments include systems and methods for analyzing images obtained from an echocardiogram. Certain embodiments include receiving video from a cardiac ultrasound of a patient illustrating at least one view the patient's heart, segmenting a left ventricle in the video, and estimating ejection fraction of the heart. Certain embodiments include at least one machine learning algorithm.

公开(公告)号：US20230346288A1

公开(公告)日：2023-11-02

申请号：US18309648

申请日：2023-04-28

申请人： The Board of Trustees of the Leland Stanford Junior University

发明人： John Weston Hughes ,  James Zou ,  Euan A. Ashley ,  Marco V. Perez

IPC分类号： A61B5/346 ,  A61B5/00 ,  G16H50/30

CPC分类号： A61B5/346 ,  A61B5/7267 ,  G16H50/30 ,  A61B5/0006

摘要： Systems and methods for predicting a future cardiovascular event are provided. Electrocardiogram waveform data can be acquired and utilized in a trained computational model to predict a future cardiovascular event. Clinical interventions, clinical surveillance, and clinical treatments can be performed based on a future cardiovascular event prediction.

公开(公告)号：US20210304410A1

公开(公告)日：2021-09-30

申请号：US17218052

申请日：2021-03-30

申请人： The Board of Trustees of the Leland Stanford Junior University

发明人： David Ouyang ,  Bryan He ,  James Zou ,  Euan A. Ashley

IPC分类号： G06T7/10

摘要： Various embodiments are directed to video-based deep learning evaluation of cardiac ultrasound that accurately identify cardiomyopathy and predict ejection fraction, the most common metric of cardiac function. Embodiments include systems and methods for analyzing images obtained from an echocardiogram. Certain embodiments include receiving video from a cardiac ultrasound of a patient illustrating at least one view the patient's heart, segmenting a left ventricle in the video, and estimating ejection fraction of the heart. Certain embodiments include at least one machine learning algorithm.