Modelling and Control in Biomedical Systems

Abstract

(partial) Plenary lectures: Biomodel formulation and identification using optimal and other effective experiment designs, J J DiStefano III. Closed loop control of physiological variables, P G Katona. The role of models in metabolic research: a physiological perspective, R R Wolfe et al. Compartmental modelling, J A Jaquez. The role of nonlinear models in neurophysiological systems analysis, V Z Marmarelis. Artificial intelligence: a new approach to modeling and control, B J Kuipers. Identification and experiment design: Estimation approaches for modeling sparse data systems, D Z D'Argenio & D C Manev l. Qualitative and quantitative experiment design for nonlinear models, E Walter & L Pronato Parameter estimation versus system structure, B Bona et al. Unidentifiable systems: an approach to structural parameter bounds, L D'Angio & S Audoly. Issues on the robust design of experiments for the estimation of nonlinear parameters, L Endrenyi et al. The future role of mathematical models in medicine: a case study, R L Flood & E R Carso . A mathematical model for time-varying pharmacokinetics, K R Godfrey. Parameter bounding for classification of drug responses, J P Norton & S H Mo. more direct approach to compartmental modelling, J Rosenblatt. Optimal sampling schedule design may reveal inadequacy of model structure: a case study on the minimal model of glucose disappearance, A Ruggeri & C Cobelli Optimized improvement of convergency in least squares parameter estimation of biomedical models, A Sano. A kinetic approach to hierarchical organization in biomedical systems, J P Sutton et al. 1800 lit. refs. approx., 410 illus.