Geisinger Clinic

Tempus Labs, Inc.

Tempus Ai, Inc.

Sushravya Raghunath

Brandon K Fornwalt

Arun Nemani

Ashraf Hafez

Christopher M Haggerty

Alvaro E Ulloa-Cerna

Christopher Good

Linyuan Jing

John Pfeifer

Greg Lee

Ruijun Chen

Noah Zimmerman

Steve Steinhubl

Thomas Morland

Tanner Carbonati

Alvaro Ulloa-Cerna

A method and system for predicting the likelihood that a patient will suffer from atrial fibrillation is provided. The method includes receiving electrocardiogram data associated with the patient, providing at least a portion of the electrocardiogram data to a trained model, receiving a risk score indicative of the likelihood the patient will suffer from atrial fibrillation within a predetermined period of time from when the electrocardiogram data was generated, and outputting the risk score to at least one of a memory or a display for viewing by a medical practitioner or healthcare administrator. The system includes at least one processor executing instructions to carry out the steps of the method.

ECG based future atrial fibrillation predictor systems and methods

A method and system for predicting the likelihood that a patient will suffer from a cardiac event is provided. The method includes receiving electrocardiogram data associated with the patient, providing at least a portion of the electrocardiogram data to a trained model, receiving a risk score indicative of the likelihood the patient will suffer from the cardiac event within a predetermined period of time from when the electrocardiogram data was generated, and outputting the risk score to at least one of a memory or a display for viewing by a medical practitioner or healthcare administrator. The system includes at least one processor executing instructions to carry out the steps of the method.

Artificial intelligence based cardiac event predictor systems and methods

Growing community of inventors

Danville, PA, United States of America

Sushravya Raghunath