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US Patent 11961004 Predicting brain data using machine learning models

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Is a
Patent
Patent
0

Patent attributes

Patent Jurisdiction
United States Patent and Trademark Office
United States Patent and Trademark Office
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Patent Number
119610040
Patent Inventor Names
Peter James Nicholas0
Stephane Philippe Doyen0
Michael Edward Sughrue0
Date of Patent
April 16, 2024
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Patent Application Number
174819500
Date Filed
September 22, 2021
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Patent Citations
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US Patent 9747421 Multi-factor brain analysis via medical imaging decision support systems and methods
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US Patent 11631000 Training artificial neural networks based on synaptic connectivity graphs
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US Patent 8742754 Method and system for diffusion tensor imaging
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US Patent 11475276 Generating more realistic synthetic data with adversarial nets
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Patent Primary Examiner
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Russell S Negin
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CPC Code
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A61B 5/377
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A61B 5/7257
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A61B 5/7267
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G16H 20/30
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G16H 20/40
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G16H 30/20
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G16H 30/40
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G16H 50/20
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Patent abstract

Methods, systems, and apparatus, including computer programs encoded on computer storage media, for predicted brain data of a patient. One of the methods includes receiving montage configuration data for a specified montage; receiving raw EEG data captured using the specified montage from a brain of a particular subject; generating, using the montage configuration data and the raw EEG data, EEG connectivity data for the specified montage; using a generative neural network to map the EEG connectivity data to predicted fMRI connectivity data, the generative neural network having been trained using training EEG-fMRI connectivity data pairs, each pair comprising EEG connectivity data of a subject and fMRI connectivity data of the same subject; and taking an action based on the predicted fMRI connectivity data.

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