A Computational Framework for Personalised Modelling. Applications in Bioinformatics

Abstract

The chapter presents a computational framework for building personalised models (PM) for accurate prediction of an outcome for the individual. First, a general scheme for building PM using integrated feature and model parameter optimisation is presented. The framework is used to develop two specific methods using: (a) traditional ANN techniques; (b) using evolving spiking neural networks (eSNN). Both methods are illustrated on benchmark biomedical data.