Medical Premonitory Event Estimation

Abstract

A system and method for medical premonitory event estimation includes one or more processors to perform operations comprising: acquiring a first set of physiological information of a subject, and a second set of physiological information of the subject received during a second period of time; calculating first and second risk scores associated with estimating a risk of a potential cardiac arrhythmia event for the subject based on applying the first and second sets of physiological information to one or more machine learning classifier models, providing at least the first and second risk scores associated with the potential cardiac arrhythmia event as a time changing series of risk scores, and classifying the first and second risk scores associated with estimating the risk of the potential cardiac arrhythmia event for the subject based on the one or more thresholds.

Description

CROSS REFERENCE TO RELATED APPLICATIONS[0001]This application claims priority under 35 U.S.C. §119(e) to U.S. Provisional Application Ser. No. 62 / 080,083, entitled “MEDICAL PREMONITORY EVENT ESTIMATION”, filed on Nov. 14, 2014; U.S. Provisional Application Ser. No. 62 / 096,140, entitled “MEDICAL PREMONITORY EVENT ESTIMATION”, filed on Dec. 23, 2014; and U.S. Provisional Application Ser. No. 62 / 235,911, entitled “MEDICAL PREMONITORY EVENT ESTIMATION”, filed on Oct. 1, 2015, the entire contents of all of which are incorporated herein by reference.BACKGROUND[0002]1. Technical Field[0003]The present invention relates to medical premonitory event estimation and detection systems and methods and, in some embodiments, to systems and methods for calculating an event estimation of risk score associated with a potential medical event for a subject.[0004]2. Description of Related Art[0005]There are many patients at risk for sudden death as a result of cardiac tachyarrhythmia induced sudden card...

AI Technical Summary

Benefits of technology

The present invention provides a medical premonitory event estimation system that uses physiological parameter data, such as ECG data, to calculate the risk score of a potential medical event, such as a cardiac event, for a subject within a specific time period. The system can also use additional data, such as image or audio data, to enhance the accuracy of the risk score estimation. The system can provide a response to the potential medical event based on the risk score, which may include informing the subject of advanced diagnostics, advising them to remove equipment, or preparing a device for treatment. The system can also update the risk score estimation based on historical patient data to improve accuracy.

Problems solved by technology

There are many patients at risk for sudden death as a result of cardiac tachyarrhythmia induced sudden cardiac arrest or asystole.

Validated methods for determining gradation of risk within these populations that would lead to recognition of early warning signs prior to onset of sudden cardiac death are lacking.

In the absence of reliable methods for classification of subjects for elevated risk, the treatment recommendations available for these patients frequently involve hospitalization and prescription of drug therapy followed by observation.

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