WINSTODEC: a stochastic deconvolution interactive program for physiological and pharmacokinetic systems
Giovanni Sparacino1, Gianluigi Pillonetto, Massimo Capello
1Dipartimento di Elettronica ed Informatica, Università di Padova, Via Gradenigo 6/A, 35131, Padova, Italy.
Abstract:
Deconvolution allows the reconstruction of non-accessible inputs (e.g. hormone secretion rate) from their causally-related measurable effects (e.g. hormone plasma concentration). Deconvolution is challenging under several aspects both general (e.g. determination of a suitable trade-off between data fit and solution smoothness in order to contrast ill-conditioning, assessment of the confidence intervals) as well as specific of physiological systems (e.g. non-uniform and infrequent data sampling). Recently, a stochastic regularization approach has been proposed and validated to handle these difficulties (De Nicolao et al., Automatica 33 (1997) 851-870). In this paper, an interactive program, WINSTODEC, is presented to allow the clinical investigator to easily obtain the solution of a deconvolution problem by this approach.
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