Modelling Optimization and Control of Biomedical Systems PDF ebook Free
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By Efstratios N. Pistikopoulos (Editor), Ioana Nascu (Editor), Eirini G. Velliou (Editor)
Shows the newest developments in the field of multi-parametric model predictive control and optimization and their application for drug delivery systems
This book is based on the Modelling, Control and Optimization of Biomedical Systems (MOBILE) project, which was created to derive intelligent computer model-based systems for optimization of biomedical drug delivery systems in the cases of diabetes, anaesthesia, and blood cancer. These systems can ensure reliable and fast calculation of the optimal drug dosage without the need for an online computer—while taking into account the specifics and constraints of the patient model, flexibility to adapt to changing patient characteristics and incorporation of the physician’s performance criteria, and maintaining the safety of the patients.
Modelling Optimization and Control of Biomedical Systems covers: mathematical modelling of drug delivery systems; model analysis, parameter estimation, and approximation; optimization and control; sensitivity analysis & model reduction; multi-parametric programming and model predictive control; estimation techniques; physiologically-based patient model; control design for volatile anaesthesia; multiparametric model based approach to intravenous anaesthesia; hybrid model predictive control strategies; Type I Diabetes Mellitus; in vitro and in silico block of the integrated platform for the study of leukaemia; chemotherapy treatment as a process systems application; and more.
- Introduces readers to the Modelling, Control and Optimization of Biomedical Systems (MOBILE) project
- Presents in detail the theoretical background, computational tools, and methods that are used in all the different biomedical systems
- Teaches the theory for multi-parametric mixed-integer programming and explicit optimal control of volatile anaesthesia
- Provides an overview of the framework for modelling, optimization, and control of biomedical systems
This book will appeal to students, researchers, and scientists working on the modelling, control, and optimization of biomedical systems and to those involved in cancer treatment, anaesthsia, and drug delivery systems.
- Hardcover:328 pages
- Publisher:Wiley; 1 edition (January 9, 2018)
A great challenge when dealing with severe diseases, such as cancer or diabe- tes, is the implementation of an appropriate treatment. Design of treatment protocols is not a trivial issue, especially since nowadays there is significant evidence that the type of treatment depends on specific characteristics of indi- vidual patients. In silico design of high‐fidelity mathematical models, which accurately describe a specific disease in terms of a well‐defined biomedical network, will allow the optimisation of treatment through an accurate control of drug dosage and deliv- ery. Within this context, the aim of the Modelling, Control and Optimisation of Biomedical Systems (MOBILE) project is to derive intelligent computer model‐ based systems for optimisation of biomedical drug delivery systems in the cases of diabetes, anaesthesia and blood cancer (i.e., leukaemia). From a computational point of view, the newly developed algorithms will be able to be implemented on a single chip, which is ideal for biomedical applica- tions that were previously off‐limits for model‐based control. Simpler hardware is adequate for the reduced on‐line computational requirements, which will lead to lower costs and almost eliminate the software costs (e.g., licensed numerical solvers). Additionally, there is increased control power, since the new MPC approach can accommodate much larger – and more accurate – biomedical system models (the computational burden is shifted off‐line). From a practical point of view, the absence of complex software makes the implementation of the controller much easier, therefore allowing its usage as a diagnostic tool directly in the clinic by doctors, clinicians as well as patients without the requirement of specialised engineers, therefore progressively enhancing the confidence of medical teams and patients to use computer‐aided practices. Additionally, the designed biomedical controllers increase treatment safety and efficiency, by carefully applying a “what‐if” prior analysis that is tai- lored to the individual patient’s needs and characteristics, therefore reducing treatment side effects and optimising the drug infusion rates. Flexibility of the device to adapt to changing patient characteristics and incorporation of the physician’s performance criteria are additional great advantages.