Invention Grant
- Patent Title: Training neural networks of an automatic clinical workflow that recognizes and analyzes 2D and doppler modality echocardiogram images
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Application No.: US16833001Application Date: 2020-03-27
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Publication No.: US11301996B2Publication Date: 2022-04-12
- Inventor: James Otis Hare, II , Paul James Seekings , Su Ping Carolyn Lam , Yoran Hummel , Jasper Tromp , Wouter Ouwerkerk , Zhubo Jiang
- Applicant: EKO.AI PTE. LTD.
- Applicant Address: SG Singapore
- Assignee: EKO.AI PTE. LTD.
- Current Assignee: EKO.AI PTE. LTD.
- Current Assignee Address: SG Singapore
- Agency: Schwabe, Williamson & Wyatt, PC
- Main IPC: G06T7/00
- IPC: G06T7/00 ; G16H40/67 ; G16H40/63 ; G16H30/40 ; G16H30/20 ; G06T7/11 ; G06N3/08 ; G06N3/04

Abstract:
A method for training neural networks of an automated workflow performed by a software component executing on a server in communication with remote computers at respective laboratories includes downloading and installing a client and a set of neural networks to a first remote computer of a first laboratory, the client accessing the echocardiogram image files of the first laboratory to train the set of neural networks and to upload a first trained set of neural networks to the server. The process continues until the client and the second trained set of neural networks is downloaded and installed to a last remote computer of a last laboratory, the client accessing the echocardiogram image files of the last laboratory to continue to train the second trained set of neural networks and to upload a final trained set of neural networks to the server.
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