Patent ID: 7801839
Filing Date: 2010-09-21
Classification: G16H

Abstract:
1. A method for training at least one artificial learning-capable system comprising the steps of: providing a predetermined training data set comprising a predetermined input data set and a predetermined outcome data set corresponding to input data for each of a respective predetermined number of subjects, observing survival data relating to patient survival of J subjects, recording covariates denoted x recording special covariates denoted z assuming each subject represents a random sample drawn from a large pool of subjects with identical covariates x, z, defining the conditional probability S(t|x,z) for surviving to time t given x, z, estimating the p-th propensity score φ categorizing the propensity scores into a number N augmenting the input data set and/or the outcome data set by the propensity scores and/or the stratum categorization, and training each artificial learning-capable system using the augmented input data set and/or the augmented outcome data set that was augmented according to the augmenting step, through the use of a computing device.