Patent ID: 6306087
Filing Date: 2001-10-23
Classification: G01N,G16H,Y10S

Abstract:
A method for constructing a computer-based neural network based classifier for the diagnosis and prognosis of a disease for use in a trained neural network, comprising:initially selecting primary biomarker inputs for the neural network that are relevant to the disease, wherein selecting the relevant biomarkers are dependent upon current biomedical science;testing for discriminating power of the selected primary biomarker inputs and removing any biomarker input that does not exhibit discriminating power;grouping the primary biomarker inputs having like properties into subsets;preprocessing the primary biomarker inputs by combining at least two primary biomarker inputs to create secondary biomarker inputs;testing the discriminating power of the primary and secondary biomarker inputs;selecting the primary and secondary biomarker inputs with the highest discriminating power;creating neural network-based classifiers by combining the selected primary and secondary biomarker inputs;evaluating an individual neural network-based classifier against test data to rank the contribution of the individual primary and secondary biomarker inputs; andselecting the best trained neural network classifier.