This book will help engineers and clinicians to: select a regression technique which can capture both linear and non-linear dynamics in glucose metabolism in diabetes, and which exhibits good generalization performance under stationary and ...

eBook Title: Personalized Predictive Modeling in Type 1 Diabetes
Author:Eleni I. Georga,Dimitrios I Fotiadis,Stelios K. Tigas
Published on 2017-12-11 by Academic Press


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Personalized Predictive Modeling in Diabetes features state-of-the-art methodologies and algorithmic approaches which have been applied to predictive modeling of glucose concentration, ranging from simple autoregressive models of the CGM time series to multivariate nonlinear regression techniques of machine learning. Developments in the field have been analyzed with respect to: (i) feature set (univariate or multivariate), (ii) regression technique (linear or non-linear), (iii) learning mechanism (batch or sequential), (iv) development and testing procedure and (v) scaling properties. In addition, simulation models of meal-derived glucose absorption and insulin dynamics and kinetics are covered, as an integral part of glucose predictive models. This book will help engineers and clinicians to: select a regression technique which can capture both linear and non-linear dynamics in glucose metabolism in diabetes, and which exhibits good generalization performance under stationary and non-stationary conditions; ensure the scalability of the optimization algorithm (learning mechanism) with respect to the size of the dataset, provided that multiple days of patient monitoring are needed to obtain a reliable predictive model; select a features set which efficiently represents both spatial and temporal dependencies between the input variables and the glucose concentration; select simulation models of subcutaneous insulin absorption and meal absorption; identify an appropriate validation procedure, and identify realistic performance measures. Describes fundamentals of modeling techniques as applied to glucose control Covers model selection process and model validation Offers computer code on a companion website to show implementation of models and algorithms Features the latest developments in the field of diabetes predictive modeling

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Eleni I. Georga,Dimitrios I Fotiadis,Stelios K. Tigas
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Book Details:
  1. Book was ranked at 18 by Google Books for Personalized Predictive Modeling in Type 1 Diabetes
  2. Personalized Predictive Modeling in Type 1 Diabetes published by Academic Press since 2017-12-11 with ISBNs. The book ISBN 13 Code is 9780128051467 and ISBN 10 Code is 0128051469
  3. Reading Mode in Text Status is true and Reading Mode in Image Status is true
  4. The book has "252 Pages" is Printed at BOOK underMedicalCategory
  5. Rated by Raters and have average rate at ""
  6. eBook Maturity (Adult Book) status is NOT_MATURE
  7. eBook written in en
  8. Book Preview Address: http://books.google.com/books?id=Rf8XDAAAQBAJ&printsec=frontcover&dq=Diabetes&hl=&cd=137&source=gbs_api

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