MACHINE LEARNING BASED RECONSTRUCTION OF INTRACARDIAC ELECTRICAL BEHAVIOR BASED ON ELECTROCARDIOGRAMS

Number of patents in Portfolio can not be more than 2000

United States of America Patent

APP PUB NO 20240249111A1
SERIAL NO

18624576

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ATTORNEY / AGENT: (SPONSORED)

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Abstract

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A computer-based system and process are disclosed for reconstructing the internal electrical behavior of a patient's heart based partly or wholly on the patient's electrocardiogram (ECG). The output of the process may include, for example, a cardiac activation map, and/or a representation of transmembrane potentials over time. The process advantageously does not require any medical imaging of the patient, and does not require any special medical equipment. For example, the patient's activation map and transmembrane potentials may be reconstructed based solely on a preexisting or newly-obtained 12-lead cardiac ECG of the patient. The process makes use of a machine learning model, such as a neural network based model, trained with actual and/or simulated ECGs and intracardiac electrical data (typically transmembrane potentials) of many thousands of patients. Because an insufficient quantity of such data exists for actual patients, model training may be performed using ECGs and intracardiac electrical data obtained through computer simulations.

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Patent Owner(s)

Patent OwnerAddress
L LIVERMORE NAT SECURITY LLC2300 FIRST STREET SUITE 204 LIVERMORE CA 94550 94550

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Inventor(s)

Inventor Name Address # of filed Patents Total Citations
Anirudh, Rushil Dublin, US 8 19
Blake, Robert C Mountain House, US 3 4
Landajuela, Mikel L Dublin, US 2 0
O'Hara, Thomas J Alameda, US 8 188

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