Patent Document ID: 9775533
Application ID: 13791764
Patent Flag: 1

Claim One:
1. A system for determining a risk score for a triage, comprising: a first input device for measuring a first input parameter relating to physiological data of a patient, the first input parameter comprising a vital signs parameter; a twelve-lead electrode electrocardiogram (ECG) device, for carrying out an electrocardiography procedure on the patient, and establishing an ECG obtained from results of the electrocardiography procedure, the ECG device comprising an ECG extraction module to extract at least one ECG parameter from the ECG; a heart rate variability (HRV) analysis module for determining a HRV analysis from the ECG, the HRV analysis comprising at least one HRV parameter; and an ensemble-based scoring system, comprising: a plurality of weighted classifiers for providing a risk score calculation, the plurality of weighted classifiers established based on past patient data in a database of accumulated past patient data; and an analysis module for receiving the first input parameter, the at least one HRV parameter, and the at least one ECG parameter which are communicated or transmitted to the ensemble-based scoring system, a sorting module arranged to receive data from the database of accumulated past patient data, and sort the data into a plurality of data sets, each data set corresponding to a classifier, and comprising an imbalanced data set; a sampling module arranged to receive a first imbalanced data set corresponding to a first classifier comprising a first majority data set comprising a first number of data samples, and a first minority data set comprising a second number of data samples, from the sorting module, and extract a first majority data subset comprising a third number of samples from the first majority data set, wherein the third number of samples in the first majority data subset is equal to the second number of samples in the first minority data set; a classifier generation module for establishing the plurality of weighted classifiers based on past patient data, wherein the classifier generation module further comprises a training module arranged to receive the first majority data subset and the first minority data set from the sampling module and build a first classification model to represent the first classifier with the first majority data subset and the first minority data set; an over-sampling module arranged to receive the first majority data subset and the first minority data set from the sampling module, and create a first synthetic data set by applying a process of synthetic over-sampling with replacement on the first majority data subset and the first minority data set; and a validation module arranged to validate the first classification model against the first synthetic data set, and obtain a resultant prediction accuracy of the first classification model representing the importance of the first classifier, wherein the analysis module determines a risk score by comparing the first input parameter, the at least one HRV parameter, and the at least one ECG parameter to corresponding weighted classifiers.