A SYSTEM AND METHOD OF GENERATING A MODEL TO DETECT, OR PREDICT THE RISK OF, AN OUTCOME

摘要

A system and method of generating a model M that can detect or predict the predisposition to an outcome, for example a person's predisposition to developing a health condition such as preeclampsia, with a positive or/and negative predictive value better or equal to a predefined predictive value target, where the method factors in the impact of prevalence on test performance. The system and method employ an iterative population segregation methodology, involving at least two population segregations steps in which each step, independently, employs a probability-defined model. The first segregation step is selected from one of a rule-in probability defined model and a rule-out probability defined model, and the second segregation step is selected from the other of a rule-in probability defined model and a rule-out probability defined model. The present invention overcomes the technical limitations of existing predictive models and provides a solution to achieve a superior predictive model delivering an accurate risk prediction result, and in a less computationally intensive way. By isolating and segmenting particular population subsets according to the invention a much more robust and accurate way of detecting, or predict risk of, an outcome is achieved.