Patent ID: 8655817
Filing Date: 2014-02-18
Classification: A61B,G16H

Abstract:
1. A method for predicting patient response to treatment for a subject patient, the method comprising: generating in memory of a computer, and storing on a system database, a first level training dataset comprising a plurality of records comprising measured patient related data from a large number of patients, the measured patient related data including clinical and/or laboratory data, diagnoses of presence or absence of known disorders and data relating to patient treatment response; wherein the measured patient related data is processed to extract features from the measured patient related data to generate an extracted feature dataset; processing the extracted feature dataset to derive a feature data scheme comprising: the feature data scheme including a reduced feature dataset whose cardinality is less than that of the extracted feature dataset; the reduced feature dataset being derived by processing the data to obtain features appearing to discriminate for a useful prediction; generating, for a subject patient, a subject patient dataset including the features obtained for the reduced feature dataset; and comparing the subject patient dataset to the feature data scheme to predict a response for the subject patient by: wherein the selected diagnosis-specific treatment response model corresponds to the determined subject patient diagnosis.