The patent badge is an abbreviated version of the USPTO patent document. The patent badge does contain a link to the full patent document.

The patent badge is an abbreviated version of the USPTO patent document. The patent badge covers the following: Patent number, Date patent was issued, Date patent was filed, Title of the patent, Applicant, Inventor, Assignee, Attorney firm, Primary examiner, Assistant examiner, CPCs, and Abstract. The patent badge does contain a link to the full patent document (in Adobe Acrobat format, aka pdf). To download or print any patent click here.

Date of Patent:
Jul. 15, 2025

Filed:

Oct. 11, 2024
Applicants:

The General Hospital Corporation, Boston, MA (US);

Beth Israel Deaconess Medical Center, Inc., Boston, MA (US);

The Broad Institute, Inc., Cambridge, MA (US);

Inventors:

Patrick T. Ellinor, Ii, Brookline, MA (US);

Emily S. Lau, Boston, MA (US);

Jennifer Ho, Cambridge, MA (US);

Mostafa Al-Alusi, Cambridge, MA (US);

Paolo Di Achille, Cambridge, MA (US);

Puneet Batra, Cambridge, MA (US);

Steven Lubitz, Boston, MA (US);

Assignees:
Attorney:
Primary Examiner:
Int. Cl.
CPC ...
A61B 8/00 (2006.01); A61B 8/08 (2006.01); G06T 7/00 (2017.01); G06V 10/774 (2022.01); G06V 10/776 (2022.01); G06V 10/82 (2022.01); G06V 20/40 (2022.01); G16H 50/20 (2018.01);
U.S. Cl.
CPC ...
A61B 8/5223 (2013.01); A61B 8/0883 (2013.01); G06T 7/0012 (2013.01); G06V 10/774 (2022.01); G06V 10/776 (2022.01); G06V 10/82 (2022.01); G06V 20/41 (2022.01); G06V 20/46 (2022.01); G16H 50/20 (2018.01); G06T 2207/10016 (2013.01); G06T 2207/20081 (2013.01); G06T 2207/20084 (2013.01); G06T 2207/30048 (2013.01); G06V 2201/031 (2022.01);
Abstract

Echocardiography deep learning and cardiovascular outcomes are described. An echocardiogram analysis module may include a deep learning model to generate a video output for an input echocardiogram video, the deep learning model comprising a convolutional neural network and at least one dense layer. The echocardiogram analysis module may further include a cardiac prediction generator to generate a cardiac prediction based on video outputs generated for a plurality of input echocardiogram videos of an echocardiogram study, the cardiac prediction comprising a measurement prediction or a classification prediction.


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