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Computational mathematics and modell...
~
Boutayeb, Abdesslam.
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Computational mathematics and modelling for diabetes
Record Type:
Electronic resources : Monograph/item
Title/Author:
Computational mathematics and modelling for diabetes/ edited by Abdesslam Boutayeb, Mohamed E.N. Lamlili.
other author:
Boutayeb, Abdesslam.
Published:
Singapore :Springer Nature Singapore : : 2025.,
Description:
xviii, 339 p. :ill., digital ;24 cm.
[NT 15003449]:
Chapter 1 A Systematic Review of Mathematical Models Dealing with Diabetes Population Dynamics -- Chapter 2 Mathematical Modelling for Glucose Homeostasis and Associated Mechanisms a State-of-the-Art Review -- Chapter 3 A Comprehensive Review of Mathematical and Data-driven Models in Glucose Homeostasis and Diabetes Pathways.
Contained By:
Springer Nature eBook
Subject:
Diabetes - Mathematical models. -
Online resource:
https://doi.org/10.1007/978-981-96-1925-2
ISBN:
9789819619252
Computational mathematics and modelling for diabetes
Computational mathematics and modelling for diabetes
[electronic resource] /edited by Abdesslam Boutayeb, Mohamed E.N. Lamlili. - Singapore :Springer Nature Singapore :2025. - xviii, 339 p. :ill., digital ;24 cm. - Industrial and applied mathematics,2364-6845. - Industrial and applied mathematics..
Chapter 1 A Systematic Review of Mathematical Models Dealing with Diabetes Population Dynamics -- Chapter 2 Mathematical Modelling for Glucose Homeostasis and Associated Mechanisms a State-of-the-Art Review -- Chapter 3 A Comprehensive Review of Mathematical and Data-driven Models in Glucose Homeostasis and Diabetes Pathways.
This book is a theoretical and pragmatic tool that applies mathematical modelling in understanding and managing diabetes and related complications such as diabetes predisposition, diabetes onset, regular glycaemic monitoring, glycated haemoglobin HbA1c, diabetes homeostasis, gestational diabetes and other associated diseases and conditions. Chapters in the book provide mathematical models dealing with the dynamics of insulin/glucose, the evolution from pre-diabetes to diabetes without and with complications, gestational diabetes and the association between diabetes and benign prostatic hyperplasia. It also applies new methods such as data mining, machine learning and deep learning. By offering pragmatic examples and comprehensive reviews on mathematical models used for diabetes, this book is useful for advanced researchers, academic teachers, students, scientists and high pharmaceutical industry executives willing to start modelling.
ISBN: 9789819619252
Standard No.: 10.1007/978-981-96-1925-2doiSubjects--Topical Terms:
2062801
Diabetes
--Mathematical models.
LC Class. No.: RC660 / .C66 2025
Dewey Class. No.: 616.4620015118
Computational mathematics and modelling for diabetes
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Chapter 1 A Systematic Review of Mathematical Models Dealing with Diabetes Population Dynamics -- Chapter 2 Mathematical Modelling for Glucose Homeostasis and Associated Mechanisms a State-of-the-Art Review -- Chapter 3 A Comprehensive Review of Mathematical and Data-driven Models in Glucose Homeostasis and Diabetes Pathways.
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This book is a theoretical and pragmatic tool that applies mathematical modelling in understanding and managing diabetes and related complications such as diabetes predisposition, diabetes onset, regular glycaemic monitoring, glycated haemoglobin HbA1c, diabetes homeostasis, gestational diabetes and other associated diseases and conditions. Chapters in the book provide mathematical models dealing with the dynamics of insulin/glucose, the evolution from pre-diabetes to diabetes without and with complications, gestational diabetes and the association between diabetes and benign prostatic hyperplasia. It also applies new methods such as data mining, machine learning and deep learning. By offering pragmatic examples and comprehensive reviews on mathematical models used for diabetes, this book is useful for advanced researchers, academic teachers, students, scientists and high pharmaceutical industry executives willing to start modelling.
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Mathematics and Statistics (SpringerNature-11649)
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EB RC660 .C66 2025
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